Ph.D. THESIS - repo.pw.edu.pl

WARSAW UNIVERSITY

OF TECHNOLOGY

Faculty of Electronics and Information

Technology

Ph.D. THESIS

Roman Łapszow, M.Sc.

Adaptive Antenna Model with Vertical Beamforming and Horizontal

Antenna Pattern Selectivity for 1800 MHz Bandwidth

Supervisor

Professor Józef Wiesław Modelski

Warsaw, 2013

Pobrano z http://repo.pw.edu.pl / Downloaded from Repository of Warsaw University of Technology 2021-10-02

Adaptive antenna model with vertical beamforming and horizontal antenna pattern selectivity for 1800 MHz bandwidth _____________________________________________________________________________________________________

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ACKNOWLEDGEMENTS

Without support, patients and good will of many people this dissertation would never exist.

My first thanks go to my mentor Professor Józef Modelski who kept me encourage to move my

research further and for his faith in my skills. Thanks to Stefan Żmudzin for original inspiration.

Thanks for significant contribution to Fryderyk Lewicki to my research work, helping in modeling

antenna and evaluating my various ideas. Thanks also go to Professors Andrzej Kowalski, Wojciech

Krzysztofik, Yevhen Yashchyshyn, Ryszard Zieliński and Ryszard Katulski that it is always good to

receive tempered feedback for ideas that not always are the best ones.

The work in this thesis has been helped immeasurably by collaboration with my colleagues from

Orange Group: Jacek Dobrzyński, Tadeusz Kurdziel, Aleksander Jakubczak from Orange Lab Poland,

Henk Tubbe from Mobistar, Mélanie Arnac, Hajer Khanfir, Zwi Altman from Orange Labs France,

Delphine Lelaidier, Jean-Louis Desvilles from La Turbie Antenna Measurement Labratory, Glyn

Roylance, Alan Stidwell, Ric Bailey from Orange Lab UK, Zhenning Shi from Orange Lab China.

Thanks for supporting me in my day-to-day work for guidance and inspiration go to: Benoît Graves,

Rémi Thomas, Eric Hardouin, Alain Wyns, Pierre Dubois, Alain le Cornec. Thanks for time and efforts

to Khalil Mouzhawak from NSN, Karel Sotek from Huawei. Finally thanks to Jean-Mark Conrat from

delivering interesting inputs that are important contribution to theoretical part of the research.

Foremost I am grateful to my loving wife Aga for her patience and forbearance.



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ABSTRACT

As growing demand for cellular system capacity seems to be endless a need for efficient way of

increasing cell throughput rate is focusing efforts on evaluations of available antenna techniques.

Adaptive antenna model has been proposed to meet the criteria for typical urban channel

conditions. Conclusions on antenna parameters criteria’s have been work out based on available in

literature measurements results, that were subject for analysis in this paper, and also based on work

done as a part of an active antenna system anticipation project for Orange Group.

The first step of this work is evaluation of available adaptive techniques. Simulations and system

performance prediction are prepared and further analyzed. Majority of inputs for presented analyses

are based on radio network planning tools outputs prepared for hypothetical ideal hexagonal cluster

scenarios but also for real terrestrial digital map layers with realistic 3G base stations locations

(source: Orange, NSN, ALU, Huawei). In cases where the outputs or simulations assumptions are

either not complete nor results are clear additional simulations are proposed to cross check the

presented performance values and decrease the uncertainty level.

Different antenna patterns and traffic profiles are analyzed. The deep analysis of virtual 6 sector sites

as horizontal cell split technique, vertical sectorisation, virtual sectorisation, user specific tilt and

finally horizontal beam switch with virtual vertical sectorisation have been provided. Adaptive

technique is proposed for LTE Release 10. Description of signal processing and frame structure is

presented. Limited results for complex solution are delivered, mostly based on composite elements:

horizontal beam-switch as a 6 sector implementation realized on single modular antenna and

modified virtual sectorisation with additional analysis from literature for combining technology

results.

In next step measurements of elevation and azimuth spread are provided. Data collected from

literature and additionally collected in the field (as a part of Orange program) allow to model dense

urban environment parameters that are used for definition of the input criteria for antenna model.

Additionally calculations of azimuth spread and delay spread for theoretical channel models are

presented.

Eventually a proposal of antenna model is provided as a result of above research studies. A unique

adaptive antenna design that merge cellular and UHF antenna techniques with baseband

beamforming concept allow to achieve desired parameters to utilize observed phenomena’s in urban

environment channels. Modeled antenna parameters are in line with results of theoretical channel

model calculations and physically measured data in field. Antenna model has been created using

FEKO tool for far field antenna patterns estimations. The antenna model design is now in the phase

of prototype preparation and further research works are planned.



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TABLE OF CONTENTS List of Tables ............................................................................................................................................ 9

List of Figures ......................................................................................................................................... 11

Chapter 1: Introduction ....................................................................................................................... 15

1.1 Switched beam antennas ............................................................................................................ 15

1.2 Dynamically-phased arrays ......................................................................................................... 15

1.3 Adaptive antenna arrays ............................................................................................................. 15

1.4 Revealed solutions for beam-steering techniques ...................................................................... 18

1.4.1 Generation of virtual beams based on 2 antnenas .............................................................. 18

1.4.2 Method of operating a base station and terminal ............................................................... 18

1.4.3 Two fixed-beams Tx-Diversity .............................................................................................. 18

1.4.4 Phased antenna array based on multibeam subarray ......................................................... 19

1.4.5 Community antenna system in the closed loop mode ......................................................... 19

1.4.6 Butler 4x4 matrix beamforming method ............................................................................. 19

1.4.7 Method of operating a trasmitter for horizontal sectorization ........................................... 19

Chapter 2: Dissertation Thesis ............................................................................................................. 20

2.1 Antenna modeling tool ................................................................................................................ 20

2.1.1 Method of moments ............................................................................................................ 21

2.1.2 Multilevel fast multipole method ......................................................................................... 21

2.1.3 Finite element method ......................................................................................................... 22

2.2 System level simulations ....................................................................................................... 22

2.3 Measurements and test campaigns ...................................................................................... 23

2.4 Expected range for downlink thoughput impovement ............................................................... 23

Chapter 3: Overview on current adaptive antenna techniques .......................................................... 24

3.1 Principles of beamforming .......................................................................................................... 27

3.2 General concept of adaptive antenna receiver ........................................................................... 28

3.3 General concept of adaptive antenna transmitter ..................................................................... 29

3.3 Uplink adaptive algorithms ......................................................................................................... 33

3.4 Downlink adaptive algorithms..................................................................................................... 34

Chapter 4: Antenna features analysis and simulations results ........................................................... 35

4.1 Horizontal sectorisation ........................................................................................................ 35

4.1.1 Horizontal sectorisation by splitting cell (conventional concept) ................................. 35

4.1.2 Horizontal sectorisation realized as virtual 6 sectors .................................................... 36

4.1.3 Horizontal sectorisation concept based on antenna array ........................................... 37



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4.2 Extended downtilts control ................................................................................................... 42

4.3 Vertical sectorisation ............................................................................................................. 46

4.3.1 Vertical sectorisation static simulations ............................................................................... 46

4.3.2 Vertical sectorization dynamic traffic simulations ............................................................... 51

4.3.3 Field test results ................................................................................................................... 52

4.4 Virtual vertical sectorisation ................................................................................................. 52

4.4.1 Downlink physical layer ........................................................................................................ 53

4.4.2 Uplink physical layer ............................................................................................................. 54

4.4.3 MIMO in downlink ................................................................................................................ 55

4.4.4 Radio resource management ............................................................................................... 56

4.4.5 Downlink dynamic scheduling and link adaptation .............................................................. 56

4.4.6 Virtual vertical sectorization simulations ............................................................................. 61

4.5 User specific tilt ........................................................................................................................... 66

4.6 Horizontal beam switching with VVS .......................................................................................... 69

4.6.1 Principles of horizontal beam switching with VVS ............................................................... 69

4.6.2 Simulations of VVS combined with horizontal beam-switching .......................................... 72

Chapter 5: Channel modeling and field measurements results .......................................................... 75

5.1 The existing 2D channel modelling and its constraints ............................................................... 75

5.2 3D channel modelling .................................................................................................................. 76

5.2.1 Theoretical channel model analysis ..................................................................................... 77

5.2.2 Azimuth and elevetion sperad tests ..................................................................................... 78

Chapter 6: Adaptive antenna model ................................................................................................... 91

Chapter 7: Summary and conclusions ............................................................................................... 103

7.1 Suggestions for future work ...................................................................................................... 103

7.2 Summary ................................................................................................................................... 104

Appendix A: Acronyms ........................................................................................................................ 107

Appendix B: FEKO antenna data.......................................................................................................... 111

Appendix C: Simulation conditions for 6-sector capacity analysis ...................................................... 125

Appendix D: Measurement conditions of antenna array for 6-sector ................................................ 131

Appendix E: Measurement conditions for optimal downtilts in urban environment ......................... 133

Appendix F: VS simulations conditions & details of outputs .............................................................. 135

Appendix G: Horizontal beam-steering measurements ...................................................................... 149

Bibliography ......................................................................................................................................... 155



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List of Tables

Table 1 Simulation parameters definition for Elastic Finite Traffic Round Robin Model ...................... 46

Table 2 Optimum values of outer cell downtilts for UL and DL for inner cell 19o downtilt .................. 50

Table 3 Throughput gains related to simulation modeling conditions ................................................. 51

Table 4 Numbers of PBRs in relation to LTE bandwidth ........................................................................ 53

Table 5 Codeword-to-layer mapping for transmit diversity 3GPP TS 36.211 ....................................... 58

Table 6 Comparison of 2x2 MIMO vs 4x2 MIMO with VS and VVS for low SINR .................................. 64

Table 7 VVS throughput gain results in comparison to VS (2x2 and 4x2) -Nantes ............................... 65

Table 8 Throughput gain results – comparison VVS to VS (2x2 and 4x2) -Marseille ............................ 65

Table 9 Codebook for 2 antenna ports ................................................................................................. 67

Table 10 UST pre-coded beams – calculated range of coverage for 3GPP case 1 ................................ 68

Table 11 Throughput results for UST and MIMO .................................................................................. 69

Table 12 Gain loss due to inefficiency of horizontal beam-switching ................................................... 73

Table 13 Modeled switch beam in comparison to adaptive array antenna pattern ............................ 73

Table 14 DS and AS parameters for different channel models ............................................................. 78

Table 15 Field measurement summary for DS, AS-BS, AS-MS, ES-BS, ES-MS ....................................... 89

Table 16 Phase shifting used for VVS simulations ................................................................................. 96

Table 17 VVS values for modeled antenna with 7o mechanical downtilt ............................................. 97

Table 18 Data for memory usage ........................................................................................................ 111

Table 19 Data for dielectric media ...................................................................................................... 111

Table 20 Excitation by voltage source at segment .............................................................................. 111

Table 21 Data of the voltage source No. 1- 8 ...................................................................................... 113

Table 22 Summary of losses ................................................................................................................ 114

Table 23 Values of the scattered electric field strength in the far field in H ...................................... 114

Table 24 Values of the scattered electric field strength in the far field in V ....................................... 119

Table 25 Simulation times (seconds) .................................................................................................. 124

Table 26 Parameters of the Claussen model for the shadow fading .................................................. 126

Table 27 Main parameters and simulation assumptions .................................................................... 126

Table 28 Capacity evaluations scenarios ............................................................................................. 127

Table 29 Summary of site capacities and capacity gains for 3-/ 6-sector sites ................................... 129

Table 30 Simulation vertical parameter settings ................................................................................ 136

Table 31 Dynamic simulations parameters ......................................................................................... 145

Table 32 Outputs for real network locations cluster 31 urban sites ................................................... 148

Table 33 Measured band frequencies ................................................................................................. 149



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List of Figures

Figure 1 Generic concept of adaptive antenna [1] ................................................................................ 16

Figure 2 Concept of beam-switching work out in Stockholm labs ........................................................ 19

Figure 3 Adaptive antenna techniques implementations [6]: .............................................................. 24

Figure 4 Phased array and adaptive array concepts for adaptive antennas [1] ................................... 25

Figure 5 Categories of adaptive techniques .......................................................................................... 25

Figure 6 Array matrix for adaptive antenna .......................................................................................... 26

Figure 7 Theoretical model of antenna array: illustration of plane wave incident from an angle φ on

an uniform linear array with inter-element spacing of Δx. ................................................................... 27

Figure 8 Adaptive antenna receiver general concept [1] ...................................................................... 28

Figure 9 Antenna arrays geometrics: linear, circular, 2-dimentional grid, 3-dimentional grid ............. 29

Figure 10 Adaptive antenna transmitter general concept [1]............................................................... 30

Figure 11 Spherical coordinate system: (xm, ym, zm) for the m-th antenna element ............................. 31

Figure 12 Channel preparation in LTE (for supporting 2 antenna ports) .............................................. 32

Figure 13 Overlapping in 3-sector site and 6-sector site ...................................................................... 35

Figure 14 NSN's 3-sector and 6-sector LTE BS RL30 [24] ....................................................................... 36

Figure 15 Capacity gains 6-sector site vs. 3-sector for Kathrein 65o and 33o HPBW antenna [24] ....... 36

Figure 16 Antenna pattern distortion for V6S implementation based on 4 column antenna .............. 37

Figure 17 Standard configuration for Kathrein 80010622 .................................................................... 38

Figure 18 Antenna array configuration for 6-sector site ....................................................................... 38

Figure 19 Simulated horizontal antenna pattern for 2 column array ................................................... 39

Figure 20 Measured horizontal pattern for antenna array ................................................................... 40

Figure 21 CDF function for intra-site and inter-site interference – results for antenna array ............. 40

Figure 22 CDF function for geometry factor and user throughput – results for antenna array ........... 41

Figure 23 Summary of results for in comparison to the reference Model [24] .................................... 42

Figure 24 Testbed environment – measuring point locations .............................................................. 42

Figure 25 SIR analysis for location #1 (close to the BS1) [17] ............................................................... 43

Figure 26 CDF function for SIR for fixed downtilts and with adaptation [17] ....................................... 44

Figure 27 Optimum setup for DL and UL for ISD500 and ISD1732 ........................................................ 44

Figure 28 Downlink capacity vs downtilt values (0-20) for 3GPP case1..3 ............................................ 45

Figure 29 Uplink capacity vs downtilt values (0-20) for 3GPP case1..3 ................................................ 45

Figure 30 Vertical sectorisation concept ............................................................................................... 46

Figure 31 3D antenna pattern based on 3GPP model ........................................................................... 48

Figure 32 Capacity system dependency of outer cell downtilts value in vertical sectorisation ........... 49

Figure 33 Power impact analysis on cell throughput ............................................................................ 50

Figure 34 UE power consumption in function of UL downtilt ............................................................... 51

Figure 35 Resource sharing between PDCCH and PDSCH ..................................................................... 54

Figure 36 VVS beam creation in baseband for common and traffic channels ...................................... 57

Figure 37 CRS symbols allocation for 4 antenna ports according to 3GPP TS 36.211 .......................... 58

Figure 38 CSI configuration for 8 antenna ports (normal cyclic prefix) ................................................ 60

Figure 39 CSI configuration for 8 antenna ports (extended cyclic prefix) ............................................. 60



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Figure 40 General concept of cell coverage for VVS ............................................................................. 61

Figure 41 Vertical beam pattern for VVS outer cell .............................................................................. 62

Figure 42 Vertical beam pattern for VVS inner cell ............................................................................... 62

Figure 43 Network topology used for simulations for VVS for 66 sites (Nantes) ................................. 63

Figure 44 Network topology used for simulations for VVS for 168 sites (Marseille) ............................ 63

Figure 45 CDF SINR – VS and VVS (2x2 and 4x2) ................................................................................... 64

Figure 46 Virtual beams created based on UST method (2 ports) ........................................................ 67

Figure 47 Plane beamforming with baseband unit control of 2 separate power amplifiers ................ 68

Figure 48 Baseband beamforming with dedicated power amplifiers to each antenna element ......... 68

Figure 49 Allocation of CSI for ports {7..10} for normal cyclic prefix 3GPP 136.211 ............................. 71

Figure 50 Horizontal angle spread – average 10o.................................................................................. 72

Figure 51 SINR results for horizontal and vertical steering techniques [69] ......................................... 74

Figure 52 2D channel modeling based on [35] ...................................................................................... 75

Figure 53 3D channel modeling based on [35] ...................................................................................... 76

Figure 54 Measuring locations in urban environment for 3D channel modeling ................................. 79

Figure 55 Schematic of measurement setup for testbed ...................................................................... 79

Figure 56 Aggregate directional spectra for all 10 UEs locations .......................................................... 80

Figure 57 Azimuth and elevation main paths directions ....................................................................... 80

Figure 58 Mean values for elevation (upper) and elevation spread in function of UE distance form BS

............................................................................................................................................................... 81

Figure 59 Results of for UE1 and UE7 locations of azimuth and elevations spreads ............................ 81

Figure 60 Realistic elevation spread simulation for 13 canyon-street locations .................................. 82

Figure 61 Elevation spread values obtained for canyon site configuration .......................................... 83

Figure 62 MS antenna used for measurements .................................................................................... 83

Figure 63 Distribution of azimuth spread and delay spread 3 typical channels definition ................... 84

Figure 64 Azimuth spread distribution (@BS) in function of MS distance from BS .............................. 85

Figure 65 Delay spread distribution (@BS) in function of MS distance from BS .................................. 85

Figure 66 AS-MS and ES-MS distribution .............................................................................................. 86

Figure 67 Received signals by MS in hotspots – potential locations of BS............................................ 87

Figure 68 Energy spread in horizontal plane observed on BS in delay spread window ........................ 88

Figure 69 General schematic of the antenna model ............................................................................. 91

Figure 70 Antenna model with X-polarity implementation allowing 8RxDiv ........................................ 91

Figure 71 Simulation of 3D antenna beam created by single module .................................................. 92

Figure 72 Theoretical capacity dependence vs antenna spacing model ............................................... 92

Figure 73 Antenna model concept – single module with horizontal polarity ....................................... 93

Figure 74 Vertical antenna patterns of single module .......................................................................... 94

Figure 75 Horizontal antenna patterns of single module ..................................................................... 95

Figure 76 Truncation for front-to-back ratio ......................................................................................... 95

Figure 77 Concept of signal supply to the individual dipoles for transmitter ....................................... 96

Figure 78 Vertical antenna pattern for downtilt -5o ............................................................................. 97

Figure 79 Vertical antenna pattern for downtilt -10o ........................................................................... 97

Figure 80 Vertical antenna pattern for downtilt -15o ........................................................................... 97

Figure 81 Vertical vs electrical downtilts coverage ............................................................................... 98

Figure 82 Increasing Front-to-Back ratio in high downtilts ................................................................... 98

Figure 83 Impedance |Z| 1710-1880 MHz band ................................................................................... 99



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Figure 84 Impedance Im(Z) 1710-1880 MHz band .............................................................................. 100

Figure 85 Impedance Re(Z) 1710-1880 MHz band .............................................................................. 101

Figure 86 Impedance phase(Z) 1710-1880MHz band ......................................................................... 102

Figure 87 Options for near-field tests ................................................................................................. 103

Figure 88 Anechoic chamber test configuration ................................................................................. 104

Figure 89 Simulation configuration for 3- and 6-sector site ............................................................... 125

Figure 90 Antenna patterns used for simulations ............................................................................... 127

Figure 91 Capacity simulations results for 4 scenarios for 3 sector site ............................................. 128

Figure 92 Capacity simulations results for 4 scenarios for 6 sector site ............................................. 129

Figure 93 Measurement configuration for reference case and antenna array .................................. 131

Figure 94 Dresden testbed environment ............................................................................................ 133

Figure 95 3x1 total tilt=12: 7° mechanical, 5°electrical ...................................................................... 135

Figure 96 3x2 Outer total tilt=10°: 7° mechanical, 3°electrical .......................................................... 135

Figure 97 3x2 Inner total tilt=18°: 7° mechanical, 11°electrical ......................................................... 136

Figure 98 SINR for vertical sectorisation: innercell, outercell and combined 3x2 case ...................... 137

Figure 99 UE throughput for outer cell: separated on losses <1 and gains >1 ................................... 137

Figure 100 UE throughput for inner cell: separated on losses <1 and gains >1 .................................. 138

Figure 101 Inner and outer cell size .................................................................................................... 138

Figure 102 RSSI for reference 3x1 case ............................................................................................... 139

Figure 103 RSSI for vertical sectorisation 3x2 case: outer and innercell .......................................... 139

Figure 104 Handoff area for reference case 3x1 ................................................................................. 140

Figure 105 Handoff area for reference case outer and inner cell3x2 ................................................. 140

Figure 106 Reference (3x1) SINR level Figure 107 Difference of SINR 3x1 vs 3x2 ......................... 141

Figure 108 SINR level for 3x2 case inner cell and SINR level for 3x2 case outer cell .......................... 141

Figure 109 Time transfer for 3x1 and 3x2 configuration with increasing λ and E(σ)=106 .................. 142

Figure 110 Gain throughput distribution for vertical sectorisation vs load ........................................ 142

Figure 111 UE’s distribution in static snapshot simulation ................................................................. 143

Figure 112 Simulated UE’s with mobility patterns ............................................................................. 144

Figure 113 Sample of user motion used by dynamic simulator .......................................................... 144

Figure 114 Antenna patterns (vertical and horizontal) for dynamic simulations ............................... 145

Figure 115 Best server map for 3x1 and3x2 case ................................................................................ 146

Figure 116 UL throughput gain for 31 most loaded sectors ............................................................... 147

Figure 117 DL throughput gain for 31 most loaded sectors................................................................ 147

Figure 118 Calibration configuration for 2661MHzfrequency ............................................................ 149

Figure 119 Measurement configuration for 2502.5 – 2567.5MHz frequency .................................... 150

Figure 120 Horizontal beam-steering measured results for azimuth 0o ............................................. 150

Figure 121 Horizontal beam-steering measured results for azimuth -30o .......................................... 151

Figure 122 Horizontal beam-steering measured results for azimuth +30o ......................................... 151



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Chapter 1: Introduction

Increasing demand for cellular network capacity caused the concept of adaptive antennas and beam

forming is back in scope of intensive research. Adaptive antennas applicable for LTE bands

(2600MHz, 1800MHz and 800MHz) could be an attractive solution for increasing radio resource

demand if capacity gain is proven and limited complexity (cost) of technology can be obtained. This

investigation is focused on analyzing capability of adaptive techniques and new concepts that can be

merged with specific antenna design for improving LTE throughput.

Concept of adaptive antenna is not new. Generally three majors streams can be distinguished

following a basic definition it a traditional array antenna [1]:

• Switched Beam Antennas

• Dynamically-Phased Arrays

• Adaptive Antenna Arrays

1.1 Switched beam antennas

Switched beam or switched lobe antennas are directional antennas deployed at base stations of a

cell. They have only a basic switching function between separate directive antennas or predefined

beams of an array. The setting that gives the best performance, usually in terms of received power, is

chosen. The outputs of the various elements are sampled periodically to ascertain which has the best

reception beam. Because of the higher directivity compared to a conventional antenna, some gain is

achieved. Such an antenna is easier to implement in existing cell structures than the more

sophisticated adaptive arrays, but it gives a limited improvement.

1.2 Dynamically-phased arrays

The beams are predetermined and fixed in the case of a switched beam system. A user may be in the

range of one beam at a particular time but as he moves away from the center of the beam and

crosses over the periphery of the beam, the received signal becomes weaker and an intra-cell

handover occurs. But in dynamically phased arrays, a direction of arrival (DoA) algorithm tracks the

user signal as he roams within the range of the beam that is tracking him. So even when the intra-cell

handoff occurs, the users signal is received with an optimal gain. It can be viewed as a generalization

of the switched lobe concept where the received power is maximized.

1.3 Adaptive antenna arrays

Adaptive antenna arrays can be considered the smartest of the lot. An adaptive antenna array is a set

of antenna elements that can adapt their antenna pattern to changes in their environment. Each

antenna of the array is associated with a weight that is adaptively updated so that its gain in a

particular look-direction is maximized, while that in a direction corresponding to interfering signals is

minimized. In other words, they change their antenna radiation or reception pattern dynamically to

adjust to variations in channel noise and interference, in order to improve the SNR (signal to noise



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ratio) of a desired signal. This procedure is also known as adaptive beamforming or digital

beamforming.

In this thesis a proposal of antenna model for LTE 1800 MHz has been presented. Switched beam

antenna concept with dynamically shifted array has been examined. Simplicity introduced to the

model was a result of detail channel model studies. Identification of most critical channel parameters

for vertical and horizontal plane for urban environment plus analysis of ongoing research in 3GPP on

3D channel model allow to propose relatively simple solution that has a potential to meet desired

criteria for majority of multipath environment.

Presented in thesis antenna model has been designed with close cooperation of Wrocław (Poland)

Orange Labs and with significant theoretical contribution of La Turbie (France) Orange Labs. The

antenna concept and adaptive algorithm is a subject of pending international patent application

placed by Orange Poland.

As major objective of this thesis was to find a tradeoff between solution complexity and performance

parameters a basic assumptions has been formulated as prerequisite: antenna cannot be wider than

35 cm – so no wide antenna array can be used for horizontal beam forming. Following generic

concept of adaptive antenna presented on Figure 1intensive investigation works started in 2011.

Figure 1 Generic concept of adaptive antenna [1]

In order to achieve above generic functionality the problem has been divided into 2 parts that have

different nature.

1. Creating a complex signal as contribution of number of incoherent antenna array paths is

strongly related to physics of antenna elements and antenna construction itself.

2. The concept of feedback that can be built based on performance index to allow individual

path phase and gain adjustment was covered by adaptive algorithms.

Performance index decision could be based only on received signal and the feedback control could

only adjust received signal however in this dissertation more complex algorithm has been proposed

with closed loop control of received and transmitted pattern.



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During analysis of the theoretical and field test of channel model estimation a non-symmetrical

transmit and received channel have been observed. However as multipath urban environment also

bring high angle spread of received signals this limits possibility of narrowing antenna characteristics

and also limits the ability of testing in closed loop alternative transmitting paths. Eventually algorithm

proposed in this thesis is based on LTE Release 10 signal structures to allow continuous

measurements and selection of most adequate transmitting path. This placed some simplicity by

treating uplink and downlink as symmetrical channels. But as proved in gain analysis part of the

thesis performance of such solution have still a big capacity potential and allow reduce complexity of

solution

Additional issue is the physical limitation of antenna size. In case of sophisticated algorithms with

capability of creating adaptive antenna patterns separate for downlink and uplink an extended

antenna array structure is a must which can be difficult for wide implementation. There are number

of implementations in radar system but not for cellular networks.

Investigations of the thesis were concentrated on base stations however analysis for mobile part

were also provided. The major disadvantage of promoting a reasonable solution for UE (user

equipment) is complexity of solution that require advanced algorithms (battery & power

consumption need to be also analyzed) plus size of terminal that does not allow place enough

antenna elements to create adaptive antenna characteristics for bandwidths below 2600MHz -

MIMO4x4 and MIMO8x8 solutions are considered for future implementations however no additional

gain were found for adding sophisticated adaptive algorithm in UE on current stage of research.

Analyzing alternative to proposed in thesis adaptive antenna solutions for cellular networks radio

access techniques that can bring capacity gain improvement in following research streams need to be

mentioned:

1. Small Cells offload and creating next layers of heterogeneous access network for current

cellular macro layer. This architecture can be adaptable not only for LTE but also for 3G networks.

Also offload can be realized based on WiFi standard.

2. Centralized scheduler. Increasing intelligence of base stations and implementing cooperation

between BS though X2 interface allow dynamic intercell interference coordination (ICIC) algorithms

and reduce the interference on the border of cell and increase throughput on cell edge. ICIC

algorithms and eICIC (enhanced ICIC) … have important role in building an efficient concept of

multilayer heterogenous network as Small Cells are also allowed to work not only on separate

frequencies but also reuse the macro layer (as is estimated this requires 3x more sites for small cell

layer). Interference for urban environment has been measured and impact of antenna pattern has

been analyzed in [17],[18] - field test in Dresden and Berlin indicate important role of downtilts and

vertical antenna pattern.

3. Coordinated Multiponit Processing (CoMP) is one of solutions that can increase capacity

though simultaneous transmission by antenna located on different base stations logically expanding

the concept of antenna array over physical antenna. CoMP does not exclude implementation of

adaptive antennas but can support the capacity enhancement solution as alternative to MIMO as



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described in [19]. Further a desired positive impact of high downtilts of antenna base station is

observed in user centric CoMP analysis presented in [20].

4. Eventually to above radio access architecture research stream a back-up concept is ready for

deployment base on multiplication of sectors and antenna system reconfiguration in heavy loaded

sites. 6-sector sites has been also analyzed in this Thesis as a base for horizontal beam switch.

Currently no solutions based on adaptive antenna is widely available for cellular systems. There are

some prototypes built for 3G or LTE networks. Available in literature results are very limited in this

field. Collected outputs were analysis are presented in this dissertation. The current active antenna

solution supporting 4 way diversity (with radio remote unit integrated with passive array single or

dual column) are now implemented on a wide scale (mainly US market) and might bring a significant

impact on current network performance specially improving uplink and improving coverage due to

reduction of cable and connection loss. The beam-steering techniques are still under studies. Several

concepts in this field are presented in the Thesis.

1.4 Revealed solutions for beam-steering techniques1

Based on Thomson Innovation Patent Export , 2013-05-24 (search results delivered 583 documents in

316 patent groups) – verification and selection of similar techniques have been done. It was

indicated 14 relevant solutions and the closest to the presented in the Thesis concept are shortly

described below.

1.4.1 Generation of virtual beams based on 2 antnenas

As presented in details in [39] and discussed with author of the patent (Munich 2012) the concept of

User Specific Tilt (UST) published in 2010 has still number of uncertainties. The major concerns

coexistence UST and MIMO techniques as the same codebooks are used for beamforming. Solution is

a subject for further analysis in this thesis.

1.4.2 Method of operating a base station and terminal

As presented in [82] a concept proposed by Stuttgart experts for method of operating a base station

and terminal is revealed in January this year. Base station is configured to control at least one

antenna system which comprises a plurality of antenna elements, wherein at least two antenna

elements are arranged at different vertical positions with reference to a virtual horizontal plane.

1.4.3 Two fixed-beams Tx-Diversity

The present invention in [83] (published October last year) relates to a method and an apparatus for

simultaneous transmitting diversity signals into a cell of a cellular system having narrow beams

utilizing non-coherent signal paths. The concept of 4 antenna ports and switch allocations on

transmit paths is presented on

1 Prepared based on JWP Chartered European Patent and Trade Mark Attorneys work done for evaluation of

VVS and horizontal beam-switching



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Figure 2 Concept of beam-switching work out in Stockholm labs

The main property utilized by the present invention for maintaining cell-coverage pattern control,

when radiating information in two simultaneous beams, is to use orthogonal polarization states for

the two beams. The two orthogonal polarization states may for instance constitute linear

polarization slanted at +45° and -45°, respectively.

1.4.4 Phased antenna array based on multibeam subarray

The interesting Samsung theoretical invention published in March this year is dedicated to solutions

of 6 sector site. Concept of hexagonal cube of array antennas (size not specified as only method was

described) is presented in [84]. This concept is as for now difficult to implement. This requires

physical 3.75o HPBW beam forming (total 256 beams) with effective steering. No sidelobs effect is

taken under consideration that based on measurement analysis presented in this research will cause

dramatic implementation problems. However proposed concept could be attractive for higher bands

if antenna array can be built with high number of elements.

1.4.5 Community antenna system in the closed loop mode

China Mobile Communication proposed in March last year a concept of pre-weighting processing for

2 separate signal paths. Processing units are delivering pre-weighted signal on separate antenna

arrays. General method with no methodology details, the only solution for antenna arrays provided

in this paper is for λ/2 separation for antenna array elements which is not a novel.

1.4.6 Butler 4x4 matrix beamforming method

A practical solution has been presented in [86] - by Wroclaw University of Technology and published

in May last year. Transmitted signal is divided on 4 inputs with equal amplitudes and phase shift: 45o,

135o, -45o, -135o.Further each of the shifted signals is divided on 2 with the relative phase shift 180o.

The created by this method signals are feeding 8 linear radiating elements. Created in that way

antenna pattern has the ration of main beam to the first sidelobe over 10dB. When amplitude

adjustment is allowed the ratio increase up to 20dB (theoretical value as it is assumed a full flexibility

of sidelobe suppression by 4 power amplifiers, which might be non-realistic).

1.4.7 Method of operating a trasmitter for horizontal sectorization

Presented in [87] method of forming horizontal beam in horizontal plane – antenna array is used.



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Chapter 2: Dissertation Thesis

Due to the observed capacity demand a need for solution for Active Antenna System that can be

efficient economic solution with significant capacity growth appear.

Base on above pragmatic challenge Thesis for this Dissertation has been formulated:

There is possible to build adaptive antenna for LTE for 1800 MHz band with size comparable to the

typical passive antennas and not wider than 350 mm. Such antenna with adaptive algorithm can

improve cell throughput providing significant capacity gain.

To prove above thesis there were defined number of research streams to find the most adequate

technique for adaptive algorithm and functional parameters of the antenna. As a first step analysis of

capacity gains for number of typical adaptive techniques (based on typical 3GPP antenna pattern

models) took place to formulate and precise area of further potential interest. In next step channel

modeling and test field analysis were done in order to find the typical urban environment

parameters. Eventually research has been focused on the antenna model design. Model was

simulated on the commercial platform (FEKO) used for antenna prototype simulations in far field.

Platform was provided by Wrocław Orange Labs under Fryderyk Lewicki supervision.

2.1 Antenna modeling tool

The antenna modeling tool is the major “engine” used to prove the dissertation thesis. The tool is

used widely for commercial antenna design; outputs are reliable and are a good validation point for

entire concept. The best possible scenario would be measure a prototype of the antenna (however it

is not built yet)

For evaluation of modeled antenna parameters FEKO platform was used. A high level specifications

of simulation methods that FEKO is equipped are delivered below according to [2].

The name FEKO is an abbreviation derived from the German phrase FEldberechnung bei Körpern mit

beliebiger Oberfläche (Field computations involving bodies of arbitrary shape). As the name suggests,

FEKO can be used for various types of electromagnetic field analyses involving objects of arbitrary

shapes is a software platform intended for the analysis of a wide range of electromagnetic problems.

Applications include EMC analysis, antenna design, microstrip antennas and circuits, dielectric media,

scattering analysis, etc. The kernel provides a comprehensive set of powerful computational methods

and has been extended for the analysis of thin dielectric sheets, multiple homogeneous dielectric

bodies and planar stratified media. The Method of Moments (MoM) technique forms the basis of the

FEKO solver. Other techniques such as the Multilevel Fast Multipole Method (MLFMM), the Finite

Element Method (FEM) Uniform Theory of Defraction (UTD), Geometrical Optics (GO) and Physical

Optics (PO) have been implemented to allow the solving of electrically large problems and

inhomogeneous dielectric bodies of arbitrary shape.



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2.1.1 Method of moments

The core of the program FEKO is based on the Method of Moments (MoM). The MoM is a full wave

solution of Maxwell’s integral equations in the frequency domain. An advantage of the MoM is that it

is a “source method” meaning that only the structure in question is discretized, not free space as

with “field methods”. Boundary conditions do not have to be set and memory requirements scale

proportional to the geometry in question and the required solution frequency. The following special

extensions have been included in FEKO’s MoM formulation to enable the modeling of magnetic and

dielectric media.

Surface Equivalence Principle (SEP): The SEP introduces equivalent electric and magnetic currents on

the surface of a closed dielectric body. The surface of such bodies can be arbitrarily shaped and is

discretized using triangles.

Volume Equivalence Principle (VEP): The VEP allows the creation of dielectric bodies from cuboids.

More basis functions are typically required than for the SEP, but neighbouring cuboids may have

differing electric and magnetic properties.

Planar Green’s Functions for Multilayered Media: Multilayered dielectric media may be modeled

with Greens functions, e.g. substrates for microstrip. The special Greens function formulation

implements 2D infinite planes with finite thickness to handle each layer of the dielectric. Conducting

surfaces and wires inside the dielectric layers have to be discretized, but not the dielectric layers

themselves. Metallic surfaces and wires can be arbitrarily oriented in the media and are allowed to

cross multiple layers. (Calculations using Greens functions are accelerated by using interpolation

tables.)

Thin Dielectric Sheets: Multiple layers of thin dielectric and anisotropic sheets can be analyzed as a

single layer in FEKO. Typical applications are the analysis of radome covered antennas and

windscreens of automobiles.

Dielectrically Coated Wires: FEKO implements two methods for the modeling of dielectric and

magnetic coatings on wires:

1. Popović’s formulation [3]modifies the radius of the metallic wire core to change the

capacitive loading on the wire, while simultaneously adding a corresponding inductive load. The

method is restricted in that the loss factor of the layer has to be identical to the loss factor of the

surrounding medium.

2. Pure dielectric layers (i.e. relative permeability of the layer equals that of the surrounding

medium) should be modelled with the equivalence theorem where the effect of the dielectric

layering is accounted for by a volume polarization current. The only restriction on the method is that

the layering may not bemagnetic.

Real Ground: Real ground can be modeled with the reflection coefficient approximation or the exact

Sommerfeld formulation [1]

2.1.2 Multilevel fast multipole method

The Multilevel Fast Multipole Method (MLFMM) is an alternative formulation of the technology

behind the MoM and is applicable to much larger structures than the MoM, making full-wave

current-based solutions of electrically large structures a possibility. This fact implies that it can be

applied to most large models that were previously treated with the MoM without having to change

the mesh. The agreement between the MoM and MLFMM is that basis functions model the

interaction between all triangles. The MLFMM differs from the MoM in that it groups basis functions



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and computes the interaction between groups of basis functions, rather than between individual

basis functions. FEKO employs a boxing algorithm that encloses the entire computational space in a

single box at the highest level, dividing this box in three dimensions into a maximum of eight child

cubes and repeating the process iteratively until the side length of each child cube is approximately a

quarter wavelength at the lowest level. Only populated cubes are stored at each level, forming an

efficient tree-like data structure. In the MoM framework the MLFMM is implemented through a

process of aggregation, translation and disaggregation of the different levels.

2.1.3 Finite element method

The Finite Element Method (FEM) is applicable to the modeling of electrically large or

inhomogeneous dielectric bodies, which are not efficiently solvable with FEKO’s extensions to the

MoM. The FEM is a volume meshing technique that employs tetrahedra to accurately mesh

arbitrarily shaped volumes where the dielectric properties may vary between neighboring

tetrahedra. FEM modelling is advantages in these instances because FEM solution matrices are

sparse, where MoM matrices are densely populated, making FEM matrices significantly better

scalable with frequency increase.

The FEM MoM/FEM hybridization features full coupling between metallic wires and surfaces in the

MoM region and heterogeneous dielectric bodies in the FEM region. The MoM part of the solution is

calculated first, which results in equivalent magnetic and electric currents that form the radiation

boundary of the FEM region. This hybrid technique makes use of the strengths of both the MoM and

the FEM in the following ways:

1. The MoM is used for the efficient modeling of open boundary radiating structures where no

3D space discretization is required.

2. The FEM is used for the efficient modeling of inhomogeneous dielectric bodies in terms of

field distributions inside the volume.

The results of antenna modeling (FEKO outputs) are provided in Appendix B.

2.2 System level simulations

In this thesis following simulations have been delivered and following results / conclusions were

obtained (gain is provided for average down link cell throughput):

1. 6-sector site with separate antenna 60% gain

2. Virtual 6 sector site with beam adaptation in horizontal plane 40% gain

3. Vertical sectorisation simulation:

a. Matlab based analyzer (interference studies) gain estimation 24%

b. Dynamic simulator run for 31 sectors with average gain 70%

4. Virtual sectorisation simulation for realistic Nance cluster case (66 sites) gain 33%

5. Virtual sectorisation simulation for realistic Marseille cluster case (168 sites) gain 47%

6. Dynamic traffic vertical sectorisation and dynamic traffic virtual sectorisation simulation:

SINR improvement by 10dB

Additionally separate uplink and downlink downtilts analysis and its impact on system performance

are provided. Those studies are showing importance of the precise vertical beam control and its high



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impact on system performance results. References with sources for each individual simulation are

provided in Chapter 4.

Above simulations are done on different platforms often with different assumptions with cross

checking outputs to mitigate the risk of inaccuracy. The aim is to evaluate independently adaptive

techniques that eventually are proposed for modeled antenna and with adaptive technique creates a

complex proposal for adaptive antenna system.

2.3 Measurements and test campaigns

In order to verify theoretical results of simulations 4 measurements campaign have been studied in

details:

1. Reference antenna array horizontal beam adaptation measurements: drop of gain by -31% in

comparison to 6 sector; horizontal beam switching estimated on c.a. 40% gain.

Measurements done by Techniche Universiteit Eindhoven and KPN –published 2012 [24].

2. Dresden testbed data collection for 2 urban sites – downtilts performce impact analysis.

Conclusion: high sensitivity of system performance is observed for small adjustment of downtilts on

cell edge => 2 the required range of vertical plane for vertical beam adjustment: up to 20o.

Measurements done under program sponsored by European Commission’s seventh framework

program FP7-ICT-2009 under grant agreement n° 247223 – published [17], [18].

3. Horizontal addaptive antenna measurements (prototype datils covered by NDA) – collected

data provided base for comparison prototype data to modeled beam-switching technique FEKO

simulator outputs. Modeled antenna provided better results than measured prototype in 2/3 of the

azimuths values. Measurements of prototype done by RFI [38] (2012).

4. Urban environmentt channel measurements: azimuth spread, vertical angle spread/

elevation spread, delay spread to allow build antenna tailored for urban typical conditions: modeled

antenna is within measured typical channel criterias. Measurements done by Ericsson R&D

(published on April 16th 2013 - [72]) and Orange Labs France (published 2011 - [61]).

2.4 Expected range for downlink thoughput impovement

Based on simulations and measurements results expected performance for modeled antenna for

downlink is 40-70% gain as an average cell throughput improvement comparable to conventional 3-

sector site.

2 SON related solutions with authomatic control of beam downtilting might provide promissing results



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Chapter 3: Overview on current adaptive antenna techniques An adaptive antenna concept is well known technic that have number of proven implementation in

radar applications (Figure 3) but so far with no wide visibility for cellular infrastructure

implementations. However number of theoretical is available in literature. Also prototypes appear as

early as for second generation GSM system, however size of the antenna and complexity does not

justify potential benefits.

a) b) c) Figure 3 Adaptive antenna techniques implementations [6]:

a) Airborne early-warning radar; b) Artillery hunting radar; c) GSM 900 Ericsson array antenna prototype

There are generally 2 concepts of forming adaptive array with ability to adjust beam according to the

environment. Both concepts are presented on Figure 4: A – a “beamformer” controls antenna array

using phased shift on each individual antenna elements creating desired antenna array directivity.

“Beam select” is a module that provides “intelligence” to adaptive algorithm and allow receiving

desired signal with the best wanted parameters. Phased array technique is limited to the portfolio of

antenna array patterns that can be generated by beamformer for the range of phase shift witch

acceptable beam shape. B – adaptive array is more individual way of controlling contribution of each

individual antenna element. Complex adaptive algorithm allow ability to mitigate interfering signals

and creates unique antenna characteristic that place “0” in interference directions and increase

directional gain in direction of desired signal. Above theory is well known however implementation is

non-trivial. Beamforming is typically based on weighted received signals from multiple antenna

elements combined to maximize the signal to interference and noise ratio (SINR).

Current advanced software features and active antenna hardware (passive antenna elements with

power amplifiers placed as close as possible to radiating elements to reduce wave length) combined

together provide a complex adaptive functionality that are subject of ongoing studies.

As more simplified adaptive technique a beam switching concept is considered. Use of preselected

antenna patterns for receiving signals brings simplicity. As beam switching concept consists of

number of fixed beams with one beam turned towards the desired signal it reduce the need of

analyzing number of channel parameters that need to be considered for individual beamforming in

fully adaptive antenna array algorithm.



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Figure 4 Phased array and adaptive array concepts for adaptive antennas [1]

Adaptive antenna patterns (phased or fully adaptive) with algorithms working in open loop as only

suitable to improve uplink as adaptation of beam pattern is based on the best received signal. Such

algorithms as direction of arrival are not good enough to support high demand for efficient radio

resource usage. They simply assume the symmetry of uplink (UL) and downlink (DL) channels which

in majority introduce quite significant error. Implementation of efficient adaptive antenna concept

requires close loop algorithms and feedback from the other end of the channel.

In order to adequately create transmitting pattern by adaptive antenna the alternative channels

should be evaluated by receiving part and information need to be send back to transmitting part to

allow closed loop adaptation. Creating an appropriate transmitting characteristic requires additional

complexity – due to the fact adaptive algorithms are mainly designed for base station at this stage.

Creating adaptive beams for mobile user equipment is limited by size of terminal (physical antenna

array), processor load and finally battery consumption.

Summarizing above adaptive antennas can be categorized in 3 typical types (Figure 6): switching

beams, dynamically phased arrays and fully adaptive array achieved as a result of superposition of

each individual transmitting module of 2-dimentional array matrix.

Figure 5 Categories of adaptive techniques

The adaptive array antenna transmits and receives signals in directed narrow beams. Figure 6 shows

a principle view of a multibeam array composed of a dual-polarized multibeam antenna with four



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azimuth beams in each of two orthogonal polarizations ±450 [6]. The radiating elements are aperture-

coupled microstrippatches, located in columns spaced half a wavelength apart. For each polarization,

the radiating elements in each column are vertically combined. One horizontal beam-forming

network combines the radiating element signals to beam ports: four beams with +450 polarization

and four beams with -450 polarization. A radome is placed in front of the antenna to protect it from

the environment. The same array antenna is used both to transmit and receive, and must work over

the entire system frequency band.

Figure 6 Array matrix for adaptive antenna

It has to be admitted that adaptive antenna concept works for creating the transmitting pattern and

receiving pattern of the antenna. The receiving pattern is achieved by post processing of received

signals from individual antenna elements. Creating adaptive array for UL channel is a way of taking

advantage of multi outputs of the channel model as used for MIMO techniques. However as a

fundamental prerequisite for MIMO is to capture non-coherent arrays (separate channels) in

multipath environment, for adaptive antenna beamforming algorithms is focused on capturing most

dominant path and eliminate interference of other signals. Co-existence of adaptive algorithms and

MIMO technics is possible and even required as supplementary concepts of finding dominant

direction for coherent signals and taking advantage of independent paths for non-coherent. Further

research in this area is presented in Chapter 5.

The antenna array can be implemented as a transmitting or / and a receiving array. To analyze

antenna array a number of assumptions need to be taken into account, they are as follows [1]:

• All signals incident on the receiving antenna array are composed of finite number of plane waves.

These plane waves result from the direct as well as the multipath components.

• The transmitter and the objects that cause multipaths are in the far-field of the antenna array.

• The sensors are placed closely so that the amplitudes of the signals received at any two elements

of the antenna array do not differ significantly.

• Each sensor is assumed to have the same radiation pattern and the same orientation.

• The mutual coupling between the antenna elements is assumed to be negligible. An antenna array

with its coordinates is illustrated on Figure 7.



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Figure 7 Theoretical model of antenna array: illustration of plane wave incident from an angle φ on

an uniform linear array with inter-element spacing of Δx.

Array geometry and element spacing

The inter-element spacing between the antenna elements is an important factor in the design of an

antenna array. If the elements are more than λ/2 apart, then the grating lobes appear which

degrades the array performances. Mutual coupling as an effect that limits the inter-element spacing

of an array. If the elements are spaced closely (typically less than λ/2), the coupling effects will be

larger and generally tend to decrease with increase in the spacing. Therefore, the elements have to

be far enough to avoid mutual coupling and the spacing has to be smaller than λ/2 to avoid grating

lobes. For all practical purposes, a spacing of λ/2 is preferred.

3.1 Principles of beamforming

The goal of a multi-element antenna array is to combine received signals in such a way that the ratio

of desirable to undesirable content in the array output is maximized. Multi element antenna array

technology is well-described in the literature, particularly as applied to deterministic beamforming,

null-steering, and gain-pattern computation [9], [10] as well as for adaptive antenna array processing

[1], [11], [12], [13]. There are several methods for combining the received signals in a multi-antenna

array, but the simplest conceptually is to multiply the signal vector (one sample per antenna

element) by the complex array weight vector and then to sum over the M antenna elements in the

array [8]:

(1)

The constraint or optimization criteria can be broadly classified either as maximizing the signal to

interference plus noise ratio (SINR) at the array output [14] or as minimizing the mean-square error



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(MSE) between the actual array output and the ideal array output [15]. In both of these cases, the

array adapts to maximize the desired signal and to reject interference.

3.2 General concept of adaptive antenna receiver

The elements of the reception part of an adaptive antenna are shown on Figure 8. The antenna array

contains M elements. The M signals are being combined into one signal, which is the input to the rest

of the receiver (channel decoding, etc.). As the figure shows, the smart antenna reception part

consists of four units. In addition to the antenna itself it contains a radio unit, a beam forming unit

and a signal processing unit [16].

Figure 8 Adaptive antenna receiver general concept [1]

In order to avoid unnecessarily high complexity in the signal processing the array need to have a

relatively low number of elements. This aspect has been further analyzed during antenna modeling.

Examples of different array geometries shows Figure 9. The first two structures are used for

beamforming in the horizontal plane (azimuth) only. This will normally be sufficient for outdoor

environments, at least in large cells. The first example (a) shows an one–dimensional linear array

with uniform element spacing of Δx. This structure can perform beamforming in azimuth angle within

an angular sector. This is the most common structure due to its low complexity. The second example

(b) shows a view of a circular array with angular element spacing of Δφ = 2π/M. This structure can

perform beamforming in all azimuth angles. The last two structures are used for performing two–

dimensional beamforming, in both azimuth and elevation angles. This may be desirable for indoor or

dense urban environments. The front view of a two–dimensional linear array with horizontal

element spacing of Δx and vertical element spacing of Δy. Beamforming in the entire space, within all

angles, requires some sort of cubic or spherical structure. The fourth example (d) shows a cubic



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structure with element separations of Δx, Δy and Δz. The radio unit consists of down–conversion

chains and (complex) analog to-digital converters (ADC). There must be M down-conversion chains,

one for each of the array elements. The signal processing unit will, based on the received signal,

calculate the complex weights w1, . . . ,wM with which the received signal from each of the array

elements is multiplied. These weights will decide the antenna pattern in the uplink direction.

Figure 9 Antenna arrays geometrics: linear, circular, 2-dimentional grid, 3-dimentional grid

An antenna array can be arranged in any arbitrary fashion, but the most preferred geometries are

linear and circular geometries. Linear geometry is simpler to implement than the circular geometry,

but the disadvantage is the symmetry of the radiation pattern, which is not observed the case in

circular array. However linear array with uniformly spaced sensors is the most commonly used

structure.

3.3 General concept of adaptive antenna transmitter

The transmission part of the adaptive antenna is schematically very similar to the reception part. An

illustration is shown in Figure 10. The signal is split into M branches, which are weighted by the

complex weights w1, . . . ,wM in the beam forming unit. The weights, which decide the radiation

pattern in the downlink direction, are calculated as before by the signal processing unit. The radio

unit consists of digital-to –analog converters (DAC) and the up converter chains. In practice, some

components, such as the antennas themselves will be the same as on reception. The principal

difference between uplink and downlink is that no knowledge of the spatial channel response is

available on downlink. In a time division duplex (TDD) system the mobile station and base station use

the same carrier frequency only separated in time. In this case the weights calculated on uplink will



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be optimal on downlink if the channel does not change during the period from uplink to downlink

transmission. However, this cannot be assumed to be the case in general, at least not in systems

where the users are expected to move at high speed. If frequency division duplex (FDD) is used, the

uplink and downlink are separated in frequency. In this case the optimal weights will generally not be

the same because of the channel response dependency on frequency.

Figure 10 Adaptive antenna transmitter general concept [1]

On the Figure 11 is presented the typical description of signal path coordinates: reference element at

the origin and the (xm, ym, zm). coordinates of the m-th antenna element. The signal as it travels

across the array undergoes a phase shift. The phase shift between the signal received at the

reference element and the signal received on m element can be described as:

θ (2)

where β = 2π/λ is the propagation constant in free space. This relation is applicable for a narrowband

signal. It is assumed that modulated bandwidth is much less than the carrier frequency. It further

allows us to assume that the only difference between the signal present at different elements of the

array is the phase shift and is not significantly affected by the modulation during this time. The

reference plane lie on z = 0, since the distance between the transmitting and receiving antenna is

much larger than the distance between the heights of the receiving and transmitting antenna, a wave

reaching the antenna array can be assumed to come along the horizon or with θ = 900. Therefore, the

direction-of arrival of each plane wave can be described using only azimuth coordinate φ. array

element height zm does not affect the phase difference between the reference element and element

m.



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Figure 11 Spherical coordinate system: (xm, ym, zm) for the m-th antenna element

Transmitted signal can be represented by:

(3)

where Am(t) is the magnitude and γm(t) is the phase of the signal. For single antenna plane:

(4)

Additionally am(φ) is defined as the ratio between the signal received at the antenna element m and

the signal received at the reference element:

(5)

The response of an M-elements antenna array to a traveling single plane wave coming at an angle φ

is defined as the steering vector :

(6)

For narrowband adaptive beamforming, each array element output is multiplied by a complex weight

modifying the phase and amplitude relation between the branches, and summed to give:

(7)

It can be also presented as vector:

(8)



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Where u(t)is defined as vector containing complex transmitting envelope signals and is called in literature the data or the illumination factor:

(9)

The response of the array (uniform linear array of isotropic elements) with the weighting network is

called the array factor and it is defined as:

(10)

The weighting network in an antenna array can be fixed or varying. In an adaptive array, the weights

are adapted by minimizing certain criterion to maximize the signal-to-interference plus noise ratio

(SINR) at the output of the array. Hence, the weighting network is very similar to a finite-impulse

response (FIR) filter, where the time samples are replaced by spatial samples. The weighting network

is therefore called spatial filter [1].

Typically in current prototypes of adaptive antennas radio module is integrated with passive antenna

elements. It allows reduction of feeder line loss and controlled quality of feeding line (standing wave

ratio, intermodulation products) but also realize physical creation of weighting network specified

above using the illumination factor to form the array factor. Typically antenna is constructed with 2-4

power amplifiers (PA) and 8-10 elements with 1:2 /1:3 /1:4 splitters combination. In order to provide

a closed loop beam control module with measurement and calibration function is given.

Figure 12 Channel preparation in LTE (for supporting 2 antenna ports)



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Data is provided by baseband unit (BBU) through CPRI (Common Public Radio Interface) [70] to the

antenna radio remote head (RRH), where signal is amplified but prior to this operations in baseline

are done. A typical 2 port antenna signal flow is specified on Figure 12.

In Release 10 for LTE up to 8 ports are standardized; signal processing though of scrambling,

modulation mapper, layer mapper, pre-coding, RE allocations and finally OFDM (Orthogonal

Frequency-Division Multiplexing)signal generation based on IFFT (Inverse Fast Fourier Transform) are

specified in details in [69].

3.3 Uplink adaptive algorithms

There are number of adaptive algorithms and structures proposed for the cellular applications in the

literature. In this chapter a classification of those algorithms and receivers for narrowband signal

processing is given in order to provide a comprehensive general picture for orientation in the large

number of proposed methods and technical solutions. In majority algorithms can be classified: with

processing in the space domain only and space-time (ST) receivers with processing in space and time

domains simultaneously. Spatial domain only and ST algorithms include optimization procedures in

their structure. The most popular optimization criteria are: maximum signal to interference plus

noise ration (SINR), squared function based criteria such as minimum square error (MSE), minimum

variance (MV) and maximum likelihood (ML). Further those optimization procedures are used by:

1. Direction of Arrival Based Methods. Methods based on spatial structure, that is, angle of arrival

(AoA) of the incoming signal

2. Training Signal Based Methods that use a known training signal or code to achieve the signal

processing objective

3. Signal Structure Based Methods, which exploit the temporal and/or spectral properties of the

received signals.

Adaptation methods available in each of the three main categories listed above can be grouped into:

1. Conventional methods that use only the received data to achieve the desired signal processing

objective

2. Parametric methods that use both, the received data and knowledge of the channel/data model to

achieve the desired signal processing objective.

Because parametric methods exploit the knowledge of the underlying model, their performance

depends strongly on the validity of the model itself. However, if the model is valid, then the

parametric methods easily outperform the conventional methods. Most modern signal processing

methods are parametric.

Direction of Arrival Based Methods, Training Signal Based Methods, Signal Structure Based Methods

are described in [1].



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3.4 Downlink adaptive algorithms

As uplink algorithms are focused on searching the best direction / beam to obtain the best possible

signal downlink algorithms are targeting most effective way of placing energy in channel to provide

UE the best possible signal.

Link Discrete Signal Model, Channel Estimation, Space-Time Processing Algorithm are described in

[1].

The well know and available in literature algorithms are not described here as methods commonly

used for modeling adaptive techniques. For purpose of the complementary solution for adaptive

antenna a downlink adaptive algorithm has been proposed allowing beam steering using a method

based on cell reference indicators and cell quality feedback information. This closed loop algorithm is

described in detail in Chapter 4 below.



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Chapter 4: Antenna features analysis and simulations results In order to propose an optimal solution for antenna system (including hardware and software) the

following concepts have been taken into account and analyzed in the research:

1. Horizontal sectorisation

2. Extended downtilt control

3. Vertical sectorisation (VS)

4. Virtual vertical sectorisation (VVS)

5. User specific tilt (UST)

6. Horizontal beam -switching with VVS

4.1 Horizontal sectorisation

The horizontal sectorisation results placed this feature on top of the list of the most attractive and

relatively easy for implementation. Concept of 6-secors is well known and will be shortly summarized

below [24].

4.1.1 Horizontal sectorisation by splitting cell (conventional concept)

The typical beamwidth and sidelobe attenuation for the 3-sector antenna pattern, are 65o and -20 dB

as for the 6-sector antenna pattern 33 o and -23 dB is expected. For the 3-sector-site deployment the

total overlapping region is 144o, while for the 6-sector-site deployment it increases to 192o. The

difference represents Figure 13.

Figure 13 Overlapping in 3-sector site and 6-sector site

The increase of overlapping area increase handovers. In addition, 6-sector antennas have stronger

sidelobes than 3-sector antennas, so the power radiated in the adjacent sectors is higher. The reason

is that the narrower the antenna beamwidth, the worse the sidelobe suppression. This cause

interference level increase. For efficient use of 6-sector an Inter-Cell Interference Coordinator (ICIC)

feature need to be considered. ICIC involves the intelligent coordination of Physical Resource Blocks



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(PRBs) between various neighboring cells to reduce the inter-cell interference and improve the

performance especially for cell-edge users. Although several techniques are available in literature,

the common strategy is to give up some resources in a coordinated fashion. As the resources are not

fully reused in each sector, the throughput is lower. These techniques can be adopted in the 6-

sector-site deployments to cope with the higher inter-cell interference resulting in lower capacity

gains. However the main drawback for lack of wide implementation of 6-sector sites is complexity of

installation. As presented on Figure 14 a big number of elements might be difficult to install on

typical urban site.

Figure 14 NSN's 3-sector and 6-sector LTE BS RL30 [24]

4.1.2 Horizontal sectorisation realized as virtual 6 sectors

An alternative concept to typical 6-sectors is analyzed named virtual 6-sector (V6S). As capacity gains

in traditional 6-sectors are for LTE on the level of 60%3 (details on Figure 15) V6S gain estimation is

dropping to 40%4 mainly due to antenna pattern distortion as beam steering range requires large

angle change.

Figure 15 Capacity gains 6-sector site vs. 3-sector for Kathrein 65o and 33o HPBW antenna [24]

3 Simulation conditions presented in Appendix C

4 Results based on vendor simulations (conditions not known)



__________________________________________________________________________________ PAGE 37

On Figure 16 are presented simulations results obtained by adjusting phase and amplitudes on 4

column antenna with spacing 0,6 λ. Even assuming the maximum side lobe on the level as high as

6 dB angle shift more than 30o were difficult to achieve. Additionally observed level of other

sidelobes even without angle shift (red pattern on Figure 16) indicate that concept of V6S using only

4 radiating elements is not the correct way for finding efficient solution.

Figure 16 Antenna pattern distortion for V6S implementation based on 4 column antenna

4.1.3 Horizontal sectorisation concept based on antenna array

Concept of alternative solution for 6-sector sites has been tested under project5 lead by Techniche

Universiteit Eindhoven together and KPN – a Dutch landline and mobile telecommunication company

based in Hague. Proposal of using antenna array based on 2 typical Katrhrein antenna 80010622 has

been evaluated. Single polarisation and comparison to modeled 6-sector sites were done for

reference single antenna and antenna array build of 2 side-by side columns.

The Kathrein 80010622 is a panel antenna that consists of two identical antennas placed side by side

in the same radome. Each of the two antennas is a slanted dual polarization (Xpol) multi-band

antenna that operates in the frequency range of 1.71-2.69 GHz. Each Xpol antenna consists of two

independently working slanted dipole systems, one for +45o polarization and the other for -45o

polarization. The HPBW of each Xpol antenna is 65o, making the Kathrein 80010622 a suitable sector

antenna for 3-sector-site deployments for 2 service providers (SP_1 & SP_2) as specified on Figure

17.

5 Project contributors: Matthijs Klepper, Arie Verschoor, Damiano Scanferla, Erik Fledderus, Leon Kaufmann,

Redert Steens, A.R. van Dommele, Kevin Wang [24]



__________________________________________________________________________________ PAGE 38

Figure 17 Standard configuration for Kathrein 80010622

The concept of building antenna array using second column to change antenna pattern and create narrow beam adaptable for 6-sector configuration has been realized as presented on Figure 18.

Figure 18 Antenna array configuration for 6-sector site

Following the theoretical study presented in [24] the voltage radiation pattern of a linear antenna

array is calculated as the multiplication of two factors:

(11)

where Se(θ) is the element factor and Sa(θ) is the array factor. The element factor is the voltage

radiation pattern of a single element, while the array factor is the voltage radiation pattern of an

array of K isotropic radiators. The array factor is expressed as:

(12)

According to [31]the absolute value of the array factor can be presented in following form:

(13) Power radiation pattern can be presented in the following format:



__________________________________________________________________________________ PAGE 39

(14)

Where Se,dB is the power radiation pattern of one of the element of the Kathrein 80010622 with -45o polarization, measured at a frequency of 2620 MHz and a 0o of downtilt angle.

(15) Where 20 log (Sa(θ)/K) is the normalized power radiation pattern of an array of K isotropic radiators. The power radiation pattern of the antenna array can be calculated as:

(16) On Figure 19 Se,dB is represented by red curve as element factor and Sa,dB is represented by green curve as array factor.

Figure 19 Simulated horizontal antenna pattern for 2 column array

On Figure 19 antenna pattern characteristic (total factor) us evaluated by measurements done under

conditions described in Appendix D.



__________________________________________________________________________________ PAGE 40

Figure 20 Measured horizontal pattern for antenna array

Field measurements confirmed antenna pattern for antenna array metrics has been prepared based

on theoretical outputs for model of 6-sector, standard 3-sector configuration with Kathrein

80010622, and array configurations (6-sector site with adopted antenna pattern). On Figure 21,

Figure 22 simulations results for 4 major metrics are presented (results are based on LTE system-level

simulator v1.3r427 [30] developed by the Vienna University of Technology).

The Intra-site interference is defined as the interference that a UE receives from the sectors of the

serving site averaged over simulation time and PRBs.

The Inter-site interference is defined as the interference that a UE receives from the sectors of the

neighboring sites averaged over simulation time and PRBs.

Figure 21 CDF function for intra-site and inter-site interference – results for antenna array

Geometry Factor is defined as the ratio between the desired received signal power that a UE receives

and the total amount of interference plus noise averaged over simulation time. It is expressed as:



__________________________________________________________________________________ PAGE 41

(17)

where PRX, PINT, and PNOISE represent the signal power, total amount of interference, and noise that

are received at time i, respectively. PRX includes the effect of shadow fading but excludes the fast

fading, therefore the GF is constant among the PRBs. The User Throughput for the u-th user is defined as:

(18)

Compared to Kathrein 80010622 in standard configuration, the antenna array results have lower

intra-site and inter-site interference. The reason is quite straightforward since for every horizontal

angles the gain of the antenna array is not greater than the gain of the single element, the level of

interference that is generated in the adjacent sectors or in the surrounding sites is lower. The

radiation nulls between the main lobe and the sidelobes affect the received power in the serving

sector.

Figure 22 CDF function for geometry factor and user throughput – results for antenna array

However, as the geometry factor is higher, this effect is compensated by the reduction of the

interference. Compared to the 6-sector antenna, due to the poor sidelobe attenuation, the antenna

array results in a much higher intra-site interference. In contrast, the inter-site interference is slightly

lower. This is due to the narrower HPBW and the lower maximum gain. As result, the geometry

factor and consequently the user throughput are lower.

Presented on Figure 23 summary results clearly indicate that antenna pattern has a significant impact

on system performance. The high level of sidelobes and zeros in antenna characteristic that might

create additionally coverage problem (not studied here) caused that proposed antenna array built

based on 2 column typical antenna is not significantly better than standard 3-sector configuration.



__________________________________________________________________________________ PAGE 42

Figure 23 Summary of results for in comparison to the reference Model [24]

4.2 Extended downtilts control

Adaptive antenna increase provide a high flexibility of downtilt control not only for remote elctric tilt

(RET) but also allows to distinguish values of dowtilts for specific bands, technology and finally aloow

seperete sutups for UL and DL.

Measurement campaign done in Dresden [17],[18] has been focused on optimal 3D beam adaptation

in urban environment. The major aims for the measurements were evaluation of the optimum

downtilt and possible SIR improvement in non-line of sight (NLOS) scenarios of an outdoor

deployment area.

Figure 24 Testbed environment – measuring point locations

Measurements conditions and data collection method were described in Appendix E. The general

plan of the testbed based on 2 sites located on the rooftop (c.a. 50m above the terrain) is presented

on Figure 24.

Geometrical downtilts (calculated based on location of UE to the base station) are very close to the

realistic measurements collected in the field. The hypothesis was provided in [17]: a potential reason



__________________________________________________________________________________ PAGE 43

for the phenomena is relatively high locations of both base stations and limited number of reflections

in this testbed. Another important conclusion that can be taken based on collected data in Dresden is

that in urban environment for macro layer sites optimal downtilts for measured 38 locations need to

have flexibility at least from 6 to 15o with even higher downtilts approximated to up to 19o for

locations close to the site (as location #1 –Figure 24). Further detail analysis were done for

location #1. On Figure 25 SIR values are presented for every possible downtilt combination of BS 1

and BS 2 and best serving BS assumed. The light colored bars indicate BS2 as serving BS, the dark

colored bars correspond to BS1 as serving BS.

Figure 25 SIR analysis for location #1 (close to the BS1) [17]

The maximum SIR is achieved for a downtilt of 12° at BS 1 and 14° at BS 2. Here the serving BS is BS 1.

When using BS2 as serving BS, the highest SIR can be realized with downtilts of 6° at both BS.

Flexibility of downtilts play a key role in SIR optimization. The case of uncoordinated dynamic

downtilt adaptation is considered: the UE at each measurement point is assigned to the BS and

downtilt which achieves the maximum receive power level. At the same time, it is assumed that in

the adjacent cell all possible downtilts are applied with equal distribution. A curve "uncoordinated

DT” represents this case Figure 26. A coordinated downtilt adaptation curve represents the most

optimal downtilt parameters setup desired for each measured point. It is assumed that the base

stations have full knowledge on the achievable SIRs of all possible downtilt combinations.



__________________________________________________________________________________ PAGE 44

Figure 26 CDF function for SIR for fixed downtilts and with adaptation [17]

With this knowledge the UEs at each measurement point are assigned to the BS and downtilts

leading to the maximum SIR. This actually created a modeling target for downtilt optimization

algorithms to be used for specific to user location. The subject of independent UL and DL downtilts

and potential impact on the network performance has been simulated (source OLabs). Results for

Inter Cell Distance (ISD) 500 and 1732m have been presented on Figure 27.

0 2 4 6 8 10 12 14 16 18 200

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

X: 14

Y: 0.9112

Dwonlink/Uplink Tilt: [degree]

Norm

aliz

ed C

apacity(C

ell

Thro

ughput)

Ubi Antenna:Normalized Dwonlink/Uplink Capacity (Cell Throughput)

X: 6

Y: 0.7791

ISD=500m Downlink

ISD=1732m Downlink

ISD=500m Uplink

ISD=1732m Uplink

Figure 27 Optimum setup for DL and UL for ISD500 and ISD1732

Further evaluation analysis6 has been performed to investigate the impact of optimal downtilts for

uplink and downlink is modeled urban environment. Analysis have been performed for typical site

6 Source Orange Labs



__________________________________________________________________________________ PAGE 45

were ISD size were: 500m, 1732m, 3000m. The size of cell was achieved by setting UE at the desired

distance from BS as hypothetical cell edge. Impact of downtilt setup on site capacity has been

analyzed. For each case downtilts setups were changed from 0o to 20o in step of 1o - results are

presented on Figure 28 and Figure 29 where capacity (relative to the optimum value) is presented in

function of the downtilts (downlink and uplink).

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 200

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Antenna Down-tilt Angle

DL C

apacity (

Unitary

)

DL Capacity with Different Down-tilt Angle

ISD=500m

ISD=1732m

ISD=3000m

Figure 28 Downlink capacity vs downtilt values (0-20) for 3GPP case1..3

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 200

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Antenna Down-tilt Angle

UL C

apacity (

Unitary

)

UL Capacity with Different Down-tilt Angle

ISD=500m

ISD=1732m

ISD=3000m

Figure 29 Uplink capacity vs downtilt values (0-20) for 3GPP case1..3

For each case a drop of capacity is observed as optimum downtilt value is exceeded. As in Dresden

geometrical downtilts (calculated based on location of UE to the base station) are very close to the



__________________________________________________________________________________ PAGE 46

realistic measurements: as for case with higher ISD optimal downtilt values are lower for cases with

lower IDS the optimum moves toward higher downtilts values. As beam reach zero at 11o (ISD3000)

and a complete capacity drop is observed, 12-13o (ISD1732) for 500 m cell capacity drop is not so

significant as for ISD3000 (as multipath propagation gain could be observed). For each case impact of

upper sidelobe is also observed. A second maximum appear for higher downtilt values again moved

towards higher downtilts for smaller cells. As for ISD1732 and ISD500 there is no difference for UL

and DL down tilts for ISD3000 the optimum is different by 1o. Using the optimal downtilt setup for DL

a capacity loss by 15% on UL is observed. Using the optimal downtilt setup for UL a capacity loss on

DL is 5%.

4.3 Vertical sectorisation

General concept of vertical sectorisation is based on cell split as is shown on Figure 30. Two beams

are created in elevation (vertical plan) with two different and fixed downtilts. Two different Cell IDs

are required. Full reuse of frequency/time resource in the two cells. Based on simulations and field

tests significant innercell UE’s throughput increase is observed. However no significant improvement

for outercell UE’s throughput is available. For outer cell might be degradation due to interference

increase. Vertical sectorisation increases the inter-beam interference and handover between the two

beams.

Figure 30 Vertical sectorisation concept

4.3.1 Vertical sectorisation static simulations

The theoretical traffic model has been based on Elastic Finite Traffic Round Robin Model as described

below. Parameters definitions are presented in Table 1. 3GPP case 1 has been simulated with

ISD=500m and 3GPP propagation model presented in Table (not modeling shadowing only path loss).

Table 1 Simulation parameters definition for Elastic Finite Traffic Round Robin Model

Parameter Definition Metrics

λ flow of arrival of UE to be served

by sector

-

E(σ) average packet size bits



__________________________________________________________________________________ PAGE 47

I traffic intensity m2

Ssect surface of sector bits/s/m2

P offered traffic in sector bits/s

SINRsect,i signal to interference noise ratio

of UEi in sector

dB

Tsect,i throughput of UEi in sector bits/s

THsect harmonic throughput of sector bits/s

ρsect load of sector -

Rsect throughput of UEi in sector bits/s/m2

In case the simulated used cannot be served due to limited resources in cell – it is not served at all. In

contradiction to full buffer where users are placed in queue and are waiting until resources are

released.

Offered traffic in sector can be presented as:

(19)

where I can be defined by flow of arrival of UE to be served by sector average packet size:

(20)

Load of the sector:

(21)

where THsect is defined as:

(22)

Finally the maximum sector capacity can be presented as follow:

(23)

For further evaluation of vertical sectorisation concept gain has been defined as ratio of maximum

capacity between capacity achieved for vertical sectorisation 3x2 sector and reference case 3x1:

(24)

where maximum capacity for investigated case taking into account both sub-sectors inner and outer:



__________________________________________________________________________________ PAGE 48

(25)

There is also mean transfer time has been defined for inner and outer cell:

(26)

(27)

Simulated antenna pattern has been based on [36] with additional inputs based on [37]. For

horizontal factor and vertical factor following definition of patterns can be assumed respectively:

v

dB

VE SLAA ,12min

2

3

,

(28)

Where: Am= 25dB, dB3 = 65o, θ3dB is adjustable 6.6o or 4o, SLAv = 20dB, plus θ takes into account

electric pre-tilt RET. The 3D antenna characteristic assumed for further investigation has been

presented on Figure 31.

Figure 31 3D antenna pattern based on 3GPP model

In the process of results analysis correction of antenna pattern has been required as strong

dependency of antenna characteristic to performance results were observed. Analysis has been done

based on modeling tool7 - Preliminary Static Simulator. Antenna tuned patterns were introduced to

the modeling tool. The detail characteristics and further simulations assumptions are presented in

Appendix F as well as detail results of simulations.

For Elastic Finite Traffic Round Robin Model obtained result of gain throughput is G=1.24.

Based on analysis presented in Appendix F for Preliminary Static Simulator following conclusions

have been taken:

7 source OLabs France: Dinh Thuy Phan Huy, Zwi Altman, Richard Combes



__________________________________________________________________________________ PAGE 49

1. gain is achieved for high traffic load;

2. SINR back off reduces real time services coverage;

3. power allocation of inner/outer cell is an optimization challenge;

4. gain depends on antenna diagrams;

5. gain requires high density of UEs.

4.3.1.1 DOWNTILTS SETUP IMPACT on VS

Additional evaluation has been done to verify sensitivity of outer cell downtilts. For Preliminary Static

Simulator downtilts 10o and 18o (accordingly outer and inner cell) and 12o for reference case were

used (Table 30 Simulation vertical parameter settings Table 30, page 136). In order to evaluate

optimum outer cell downtilt that has the major impact on edge coverage for further analysis two

predefined inner cell downtilt values were used: 12o and 19o. The aim was to find optimum UL and

DL downtilts for outer cell for VS.

The low downtilt (12o) for inner cell is not applicable and has been tested as a base scenario for high

overlapping inner and outer with different Cell_ID to estimate maximum interference impact in

vertical sectorisation scenario.

0 2 4 6 8 10 12 14 16 18100

200

300

400

500

600

700

X: 12

Y: 610

OuterSector Dwonlink/Uplink Tilt: [degree]

Capacity(S

yste

m T

hro

ughput)

: M

bps

Vertical Sector Dwonlink/Uplink Capacity

X: 10

Y: 355

InnerSect Tilt=19degree:Downlink

InnerSect Tilt=19degree:Uplink

InnerSect Tilt=12degree:Downlink

InnerSect Tilt=12degree:Uplink

Figure 32 Capacity system dependency of outer cell downtilts value in vertical sectorisation

The second value for inner cell downtilt (19o) was used to examine impact of outer cell downtilts changes on cell throughput. Details are delivered for 30 on Figure 32, where high sensitivity for tilts higher than optimal are observed. As specified in

Table 2 – 10o downtilt taken for Preliminary Static Simulator (for UL &DL) was an optimum value for

DL but some additional UL improvement can be expected in case of DL and UL separate

optimization.



__________________________________________________________________________________ PAGE 50

Table 2 Optimum values of outer cell downtilts for UL and DL for inner cell 19o downtilt

Optimal outer cell downtilt Simulation values

Uplink 12o 10o

Downlink 10o 10o

4.3.1.2 POWER SETUP IMPACT on VS

Additional simulation has been done to evaluate impact of power decrease from 46dBm in reference

case (3x1) to 43dBm for VS case (3x2) – as total BS power is split between inner and outer cell. This

analysis has been done for different antenna patterns then in Preliminary Static Simulator and need

to be treated separately.

Antenna pattern of 8o vertical HPBW has been proposed. No impact is observed on average cell

throughput in DL as presented on Figure 33 and on UE power as presented on Figure 34 8.

0 2 4 6 8 10 12 14 16 18 204

6

8

10

12

14

16

18

Dwonlink Tilt: [degree]

Avg.

Cell

Thro

ughput:

[M

bps]

ISD=500m: Dwonlink Capacity (Avg. Cell Throughput)

Ver.HPBW=16degree,43dBm



Figure 33 Power impact analysis on cell throughput

8 Also HPBW for 16

o beam has been checked but it is irrelevant to the presented VS gain analysis



__________________________________________________________________________________ PAGE 51

0 2 4 6 8 10 12 14 16 18 2032

34

36

38

40

42

44

46

Uplink Tilt: [degree]

Ave

rage

Ue

Pow

er:

[mw

]

ISD=500m: Average UE Power




Figure 34 UE power consumption in function of UL downtilt

The analysis of minimizing UE transmitted power (that is presented on Figure 34 in mW) caused

introduction of new value for vertical HPBW (probing 16o), however as presented results confirmed

narrow beam (8o) allows average UE power reduction due to higher gain and improved UL link

budget. Based on this simulation potential for adaptive antenna is visible: physical ability of separate

downtilts for UL and DL can be utilized to optimize throughput or/and UE power consumption. This

drives to the next wider conclusion of a potential for Self Optimizing Network (SON) solutions with

adaptive antennas if adjustable downtilts control could be done in real life. The dynamically

adjustable downtilts can optimize network parameters depending on traffic growth and desired

parameter optimization.

4.3.2 Vertical sectorization dynamic traffic simulations

Dynamic load of simulated cell for Full Buffer traffic has been used. Details are presented in Appendix

F. Dynamic Simulator results run on realistic terrain and realistic site locations provide throughput

G=1.45 (DL) and G=1.79 (UL). Using Preliminary Static Model with option for Full Buffer Traffic Model gain of G=1.55 (DL) has been

obtained.

Summarizing - throughput gains are traffic model depended, traffic location depended (coverage and

terrain), antenna pattern depended and downtilts depended. Aggregation of those dependencies for

VS simulations are presented on Table 3.

Table 3 Throughput gains related to simulation modeling conditions

Simulation Type

Traffic Simulation

DL throughput gains UL throughput gain

Optimal downtilts inner / outer cell

Reference case downtilt

STATIC Full Buffer 1.51-1.55 1.76 15o/5o 5o

Finite Elastic Traffic

1.24 - 18o /10o 12o

DYNAMIC Full Buffer 1.45 1.79 15o/5o 5o



__________________________________________________________________________________ PAGE 52

4.3.3 Field test results

To evaluate results of simulations and theoretical analysis a field test has been done in Oulu (Finland)

on one site in suburban environment. As tests were covered by non-disclosure agreement the detail

conditions and final results cannot be presented in this Thesis. However similar test results were

done in Deutsche Telecom network with active antenna prototype for LTE 1800MHz; information has

been published on April 9, 2013 by Huawei:

http://4g-portal.com/worlds-first-advanced-active-antenna-system-trial-achieved-in-germany

The results achieved for vertical sectorisation allow obtaining up to 70% throughput gain.

4.4 Virtual vertical sectorisation

Virtual sectorisation concept is based on modification of vertical sectorisation. Taking under

consideration the major drawbacks coming from interface increase, traffic dependency gains and

selectivity of implementation (only 10% of simulated sites have a potential for vertical sectorisation),

virtual vertical sectorisation (VVS) using Rel.10 standards might overcome the problems.

The concept is based on splitting only PDSCH (Physical Downlink Shared CHannel) that are assigned

to different antenna patterns dynamically according to UE location. Control channels and Cell_ID

stays the same: Cell Reference Signal (CRS)/ Physical Downlink Control CHannel (PDCCH)/ Physical

Broadcast CHannel (PBCH) are transmitted without beamforming providing base coverage. This

allows more flexibility in allocating users to inner and outer cell and does not increase interference.

Also allocated power of outer cell (which equals of entire cell in case of VVS) is 3dB higher than in

vertical sectorisation. This has impact on cell edge coverage improvement. The concept of VVS allows

also stays on the same level of handoff as no additional cell is added to radio network plan.

Detail concept of VVS:

As a first layer of adaptation introduced by VVS is a scheduler selection adapted for current load

conditions in cell. The chosen scheduler is used by both beams (entire cell). The concept of scheduler

adaptation is based on:

1. Single User (SU) scheduling for coverage

2. Multi User (MU) scheduler for capacity by frequency/time reuse

3. SU/MU switching managed by scheduler

The algorithm for choosing appropriate scheduler is starting with SU to maximizing cell edge

coverage. As the load in cell reaches the threshold, which value can be steered by Self Optimizing

Network (SON), scheduler is switched on MU.

A second layer of adaptation introduced by VVS is a dynamic load balancing between virtual inner

and outer cell by downtilts / beam pattern selection.

The coordination between above 2- layers need to be done to achieve optimum resource utilization:

as load in virtual inner cell appears it can be efficiently served by virtual inner beam. The virtual inner

cell beam serves UE’s close to the center of the site. System is taking the advantage of selected and

UE directed beam studied in vertical sectorisation; significant increase of throughput should be


http://4g-portal.com/worlds-first-advanced-active-antenna-system-trial-achieved-in-germany


__________________________________________________________________________________ PAGE 53

observed. In such case the load is efficiently served by inner beam the threshold of switching whole

cell scheduler to MU can be increased. In contradiction to above load might appear at the edge of

the cell and advantage of virtual inner beam cannot be used. As majority of the traffic is located on

the cell edge decision of switching on MU might sacrifice the number of users that might lose

coverage. If the traffic is distributed more uniformly decision to move to MU might be efficient. The

predefined value for the threshold is not appropriate solution in case VVS implementation. The

switching point need to be steered based on number of users on cell edge, traffic performance

parameters, SINR decrease.

As control of SU/MU switching point is SON related it is not further studied in this thesis. Further

analysis are done for SU-MIMO. Radio resources are not reused: a radio resource in time and

frequency is either transmitted with the inner or outer downtilt. In the analysis the sector tilts are

fixed and the number of tilts is limited to 2. This leads to a signal increase of the user (especially for

the inner cell sector users) and a reduction of the interference on the surrounding cells (especially if

an inner cell sector user is served).

In order to described the technique used for beam selection for VVS a short introduction to LTE FDD

principles is delivered below.

LTE FDD adopts a 10 ms frame structure for both downlink and uplink transmissions. Each frame is

divided in 0.5 ms slots and the shortest allocation period is 1 ms (1 subframe). The resources

consisting of 12 contiguous sub-carriers (180 kHz) and a duration of 1 ms subframe are known as

Physical Resource Block (PRB). One PRB is the smallest amount of resources that can be allocated to

one UE. Table 4 summarizes the number of available PRBs as a function of the system bandwidth.

Table 4 Numbers of PBRs in relation to LTE bandwidth

System Bandwidth (MHz)

1.4 3 5 10 15 20

Number of PRBs 6 15 25 50 75 100

4.4.1 Downlink physical layer

The multiple access scheme chosen for downlink LTE was OFDMA. Therefore each sub-carrier is

transmitted as a parallel 15 kHz sub-carrier. One 0.5 ms slot can accommodate 6 or 7 OFDM symbols

per sub-carrier, depending on whether an extended or short cyclic prefix is used. The user data in the

downlink direction is carried out on the PDSCH. Based on the Channel Quality Information (CQI)

received from the terminals, the scheduler in every BS's sector performs the resource allocation for

the active users in its serving area every subframe. The resources are allocated in both time and

frequency domain. The PRBs are not necessary having continuous allocation in the frequency

domain. The PDCCH informs the device about the PRBs that are allocated to it, dynamically with 1 ms

granularity. PDSCH data occupy between 9 and 13 symbols per 1 ms subframe depending on the

allocation for PDCCH and depending whether a short or extended cyclic prefix is used. Within the

1 ms subframe, only the first 0.5 ms slot contains PDCCH while the second 0.5 ms slot is purely for

PDSCH data. The number of symbols for PDCCH within a subframe can vary between 1 and 3. Figure



__________________________________________________________________________________ PAGE 54

35 shows an example of resource allocation for PDSCH and PDCCH along with the RS pattern that is

defined when 2 antennas are used for downlink transmissions. The figure on the left refers to the

antenna port 1, while the figure on the right refers to the antenna port 2. Note that when a resource

element is used to transmit an RS on one antenna port, the corresponding OFDM symbol on the

other antenna port is not used. The modulation methods available in PDSCH are Quadrature Phase

Shift Keying (QPSK), Quadrature Amplitude Modulation (QAM): 16QAM and 64QAM. In theory, an

OFDM system could use different modulations for each sub-carrier. However, to have CQI and

signaling with such granularity would not be feasible due to the resulting excessive overhead. Indeed,

if modulation was sub-carrier specific, there would be too many bits in the downlink for informing

the receiver of parameters for each sub-carrier and in the uplink the CQI feedback would need to be

too detailed to achieve sub-carrier level granularity in the adaption. Therefore, it was chosen to

adapt the modulation on a per user and subframe basis. Meaning that PRBs that are intended for one

user will have the same modulation. The PDCCH uses either Binary Phase Shift Keying (BPSK) or

QPSK. The channel coding chosen for LTE user data in the downlink direction was 1/3-rate turbo

coding. The encoder is Parallel Concatenated Convolution Coding (PCCC). The turbo interleaver of

WCDMA was modified to better fit LTE properties and slot structures and also to allow parallel signal

processing with increased data rates. The maximum block size for turbo encoding is limited to 6144

bits, higher allocations are then segmented to multiple encoding blocks. The instantaneous data rate

for downlink depends on the modulation, the allocated amount of PRBs, the channel encoding rate,

and the transmission mode (MIMO operation).

Figure 35 Resource sharing between PDCCH and PDSCH

4.4.2 Uplink physical layer

The multiple access scheme chosen for uplink LTE was Single Carrier Frequency Division Multiple

Access (SC-FDMA). The user data in the uplink direction is carried on the Physical Uplink Shared

Channel (PUSCH). The same 1 ms resource allocation is also valid in the uplink direction. The resource

allocation comes from a scheduler located at the BS. Based on the buffer status received from the

active users, the uplink scheduler allocates the resources and communicates the allocation to the



__________________________________________________________________________________ PAGE 55

active users. Without prior signaling from the BS, only random access resources may be used. The

allocated bandwidth to a user in a sub-frame may be between 0 and 20 MHz, in steps of 180 kHz. In

uplink, the allocation of PRBs to the active users must be contiguous. In fact only one SC-FDMA

symbol can be transmitted at a time using the entire allocated bandwidth. Conversely, we have seen

that in downlink, one OFDMA symbol per sub-carrier is transmitted at a time, thus an active users

may be assigned with not contiguous PRBs. The channel coding for user data in the uplink direction is

also turbo coding, as in the downlink direction. The instantaneous uplink user data rate depends on

the modulation, the number of PRBs allocated, the amount of control information overhead, and the

rate of channel coding applied.

4.4.3 MIMO in downlink

LTE supports up to four transmit antennas at the BS and up to four receive antennas at the UE. The

MIMO technologies adopted in downlink LTE are:

• Single-User MIMO (SU-MIMO). In SU-MIMO, the transmissions of multiple streams of data to a

given user are overlapped in the same time-frequency resources by exploiting the spatial diversity of

the propagation channel. The maximum number of supported spatial layers is two, when the

transmit and receive antennas are two, and four, when the transmit and receive antennas are four.

There are two operation modes in SU-MIMO spatial multiplexing: open-loop spatial multiplexing and

closed-loop spatial multiplexing. In the closed-loop spatial multiplexing mode, the BS applies the

spatial domain precoding on the transmitted signal taking into account the precoding matrix

indicator (PMI) reported by the UE so that the transmitted signal matches with the spatial channel

experienced by the UE. In the open-loop spatial multiplexing mode, the PMI feedback is not available

at the BS, thus a fixed set of precoding matrices are applied cyclically across all the scheduled

subcarriers in the frequency domain. To support both operation modes, the UE needs to feedback

the rank indicator (RI) in addition to the PMI. The RI indicates the number of spatial layers (rank) that

can be supported by the current channel experienced at the UE. The BS may decide the transmission

rank based on the RI reported by the UE as well as other factors such as traffic pattern, available

transmission power, etc.

• Transmit Diversity. Transmit diversity is used when the selected transmission rank is one. Thus,

switching between SU-MIMO modes is possible depending on channel conditions. In transmit

diversity only one stream of data is transmitted to a given UE. Multiple transmit antennas are used to

reduce the fading experienced at the UE rather than simultaneously transmit different streams of

data. The fading reduction is obtained by transmitting each sub-carrier symbol in two different sub-

carriers (one sub-carrier per antenna). Transmit diversity is specified for two and four transmit

antennas.

• Multi-User MIMO (MU-MIMO). As in SU-MIMO, multiple antennas are used to transmit different

streams of data in the same time-frequency resources. However, while in SU-MIMO different

streams are transmitted to a given user, in MU-MIMO different streams are transmitted to different

users. Since transmissions to several terminals are overlapped in the same time-frequency resources,

MU-MIMO aims to enhance the capacity of a cell, rather than increasing the user peak rate. In order

to fully exploit MU-MIMO transmission modes, the spatial streams intended to the targeted

terminals need to be well separated, ideally orthogonal at both transmit and receive sides.

• Closed-loop rank-1 precoding. In the closed-loop rank-1 precoding mode, the BS operates the

closed-loop SU-MIMO scheme based on the cell-specific common reference signal with the limitation



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of selecting a rank-1 precoding matrix for transmission to a UE among the ones defined for two and

four transmit antennas. The aim is to improve data coverage without relying on the UE-specific

reference signal. Further, since the transmission rank is fixed, the related control signaling overhead

is smaller than the case of operating the closed-loop SU-MIMO scheme.

• Dedicated beamforming. Dedicated beamforming is used to improve data coverage when the UE

supports data demodulation using the UE-specific reference signal. The BS generates a beam using

the array of antenna elements, and then applies the same precoding to both the data payload and

the UE-specific reference signal with this beam

4.4.4 Radio resource management

The role of Radio Resource Management (RRM) is to ensure that the radio resources are efficiently

used, taking advantage of the available adaptation techniques, and to serve the users according to

their configured Quality of Service (QoS) parameters. The family of RRM algorithms at the BS exploits

various functionalities from Layer 1 to Layer 3 as listed below:

• Layer-3 : QoS management, Admission control, Persistent scheduling;

• Layer-2 : Dynamic scheduling, Link adaptation;

• Layer-1 : PDCCH adaptation, CQI manager, Power control.

The RRM functions at Layer 3 are characterized as semi-dynamic mechanisms, since they are mainly

executed during setup of new data. Instead, the RRM algorithms of Layer 1 and Layer 2 are highly

dynamic functions with new actions conducted every Transmission Time Interval (TTI). The CQI

manager processes the received CQI reports and Sounding Reference Signals (SRSs) from active users

in the cell. The CQI report is related to the channel conditions experienced at the UE in downlink and

indicate a combination of modulation scheme and channel coding rate that the BS should use to

ensure that the block error rate probability at the UE will not exceed 10%. The SRSs are used in uplink

in order for the BS to be able to estimate the channel condition in uplink. Each received CQI report

and SRS is used by the BS for scheduling decision and link adaptation in downlink and uplink,

respectively.

4.4.5 Downlink dynamic scheduling and link adaptation

The dynamic packet scheduler (PS) and the link adaptation entity (LA) are Layer 2 RRM entities. The

PS performs scheduling decisions every TTI by allocating PRBs to the users, while the LA selects the

modulation and coding scheme based on the CQI reported by the UEs. The allocated PRBs and the

selected modulation and coding scheme are signaled to the scheduled users on the PDCCH. The

overall packet scheduling goal is to maximize the cell capacity, while making sure that the minimum

QoS requirements for the EPS bearers are fulfilled and there are adequate resources also for best-

effort bearers with no strict QoS requirements.

The first step of packet scheduling is the time-domain packet scheduler (TDPS). From the set of active

users for which data is available for transmission, the TDPS selects a subset of M users for which

resources have to be allocated in the TTI being scheduled. This subset forms the candidate set of

users for the frequency-domain packet scheduler (FDPS). For each UE, the TDPS calculates a

scheduling criterion. Further in second step - the FDPS allocates the available PRBs to the users

selected by the TDPS. The FDPS principle exploits the frequency selective power variations of the

received signal by only scheduling users on the PRBs with high channel quality, while avoiding the

PRBs where a user experiences deep fades. The overall objective of FDPS is to maximize the benefit



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from the frequency selectivity, while still guaranteeing certain fairness. The FDPS is responsible for

allocating the PRBs to users with new transmissions and also to users with pending retransmissions.

The CQI value is used to inform BS by UE about the preferable beam and allow selection of the DL

beam as a part of RRM layer 1 algorithm. The same beam is used for UL as symmetric DL/UL channel

is assumed. UE receives CSI from the specific beam which allows easy comparison of received signal

strength indicator (RSSI) and close the loop of adaptation. As described on Figure 36 3 set of beams

are created in baseband for each VVS sector splitting the cell on virtual inner and outer cell, however

no reuse of resources is allowed as Cell_ID stays the same (SU-MIMO):

set ”i”: common channels are mapped on resource element (RE) and coverage beam is created

set “j”: PDSCH is mapped on RE for inner cell

set ”k”: PDSCH is mapped on RE for outer cell

Figure 36 VVS beam creation in baseband for common and traffic channels

Allocation to specific beam can be done in various way based on several available reference signals in

Release 10. There are five types of downlink reference signals:

- Cell-specific reference signals (CRS)

- MBSFN reference signals

- UE-specific reference signals (DM-RS)

- Positioning reference signals (PRS)

- CSI reference signals (CSI-RS)

There is one reference signal transmitted per downlink antenna port and for beam allocation CSR,

DM-RS, CSI will be further presented. The target configuration is presented on Figure 36 with CSI

reference signals but in case of backward compatibility the need of adopting typical Release 8

structure based on CRS might appear. Beam selectivity based on CRS allows up to 4 antenna ports

mapping. In such case Port 0 can be used for caring Rel.8 traffic (set “i” coverage beam no VVS). The

first 3 PBR’s in each block (for ports 0..2) need to be allocated to set”i” as control channels to secure

signaling communications and unified Cell_ID for inner and outer part of the cell. Set “j” can be



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allocated to Port 1 for inner cell traffic and set “k” to Port 2 for outer cell traffic. Port 3 in such case is

not used. Allocation of CRS is done according to 3GPP TS 36.211 for 4 antenna ports; presented on

Figure 37.

Figure 37 CRS symbols allocation for 4 antenna ports according to 3GPP TS 36.211

The major drawback of the VVS concept when only CRS is used is limitation to 4 ports that were

originally reserved for transmitting diversity. In the proposed concept of utilizing predefined beams

and overall only 3 antenna ports – a single virtual sector has “equipped” with a single “channel” to

UE as only one port is used for inner and one for outer cell. The scheme is not adequate to support

antenna cross-polar diversity.

Table 5 Codeword-to-layer mapping for transmit diversity 3GPP TS 36.211

According to 3GPP standardization for transmit diversity, the layer mapping shall be done according

to Table 5 Codeword-to-layer mapping for transmit diversity 3GPP TS 36.211. There is only one

codeword and the number of layers is equal to the number of antenna ports used for transmission of

the physical channel. Precoding for spatial multiplexing using antenna ports with cell-specific

reference signals is only used in combination with layer mapping for spatial multiplexing. Spatial

multiplexing supports two or four antenna ports and the set of antenna ports used is p {0,1}or

p {0,1,2,3}, respectively.

Spatial multiplexing using antenna ports with UE-specific reference signals supports up to eight

antenna ports and the set of antenna ports used is p = 7,8,..., + 6



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In such case a proposal of alternative solution can be built for up to 8 antenna ports. Standard allows

to use specified ports also for Mobile Broadcast Single Frequency Network (MBSFN) solution which

might in future limit the availability of VVS.

The final proposed concept is based on channel state information reference signal (CSI-RS) and CSR

which allow built 2x2 VVS and 4x2 VVS (eventually 4x4 if UE will support 4Tx).

CSI reference signals, available for Release 10, are transmitted on one, two, four or eight antenna

ports using p = 15, p =15,16 , p =15,...,18 and p =15,...,22 , respectively. CSI reference signals are

defined for f = 15 kHz only.

The reference-signal sequence is defined by

(29)

where ns is the slot number within a radio frame and l is the OFDM symbol number within the slot.

The pseudorandom sequence c(i) is defined by a length-31 Gold sequence. The output sequence c(n)

of length MPN ,where n 0,1,..., MPN 1, is defined:

(30)

mod2 (31)

mod2 (32)

where Nc= 1600, the pseudo-random sequence generator shall be initialized with cinit

(33)

at the start of each OFDM symbol where NCP

In subframes configured for CSI reference signal transmission, the reference signal sequence

shall be mapped to complex-valued modulation symbols according to [69]:

(34)

The quantity (k', l' ) and the necessary conditions on ns are given by Tables for normal and extended

cyclic prefix, respectively. Multiple CSI reference signal configurations can be used in a given cell

when:

- zero or one configuration for which the UE shall assume non-zero transmission power for the CSI-

RS, and

- zero or more configurations for which the UE shall assume zero transmission power.



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Figure 38 CSI configuration for 8 antenna ports (normal cyclic prefix9)

Based on presented on Figure 38 and Figure 39 configurations – following allocation are possible:

set ”i”: CRS:

antenna port {0,1} for 2x2MIMO;

antenna port {0,1,2,3} for 4x2MIMO

(no VVS in case of Release 8 traffic)

set “j”: CSI-RS PDSCH is mapped on RE for inner cell:

antenna port {15,16} for 2x2MIMO (typically one column antenna with ±45o polarization)

antenna port {19,20} for 4x2MIMO (typically two column antenna with ±45o polarization)

set ”k”: CSI-RS PDSCH is mapped on RE for outer cell

antenna port {17,18} for 2x2MIMO (typically one column antenna with ±45o polarization)

antenna port {21,22} for 4x2MIMO (typically two column antenna with ±45o polarization)

Figure 39 CSI configuration for 8 antenna ports (extended cyclic prefix)

9 The Cyclic Prefix represents a guard period at the start of each OFDMA symbol which provides protection

against multi-path delay spread. The cyclic prefix also represents an overhead which should be minimized LTE specifies both normal and extended cyclic prefix lengths. The normal cyclic prefix is intended to be sufficient for the majority of scenarios, while the extended cyclic prefix is intended for scenarios with particularly high delay spread.



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For VVS a theoretical coverage concept is presented on Figure 40. For further VVS analysis a

comparison VVS to VS for realistic traffic conditions and modeling for 2 cities have been prepared.

Figure 40 General concept of cell coverage for VVS

4.4.6 Virtual vertical sectorization simulations

Simulations were based on radio network planning tool with build in and tuned for dedicated terrain

conditions propagation models used for realistic site locations. For each city a baseline scenario and

2 scenarios for VS and 2 for VVS were done: 2x2MIMO (VS2x2, VVS2x2) and 4x2MIMO (VS4x2,

VVS4x2). For a given user, inner and outer beams share the same shadow fading, path loss and

horizontal beam pattern. Hence, the inner/outer beam selection in VVS mainly depends on the

vertical beam pattern. As shown in the Figure 40, the case of 4 o vertical HPBW with 18o inner beam

downtilt and 10o outer beam downtilt, and 20 dB vertical sidelobe gain was a base for the concept of

simplified antenna however more sophisticated models have been used that have been obtained

from first measurements of VVS prototype antenna. Vertical beam patterns for outer virtual cell are

presented on Figure 41 and for inner virtual cell on Figure 42 Horizontal pattern was not changed and

used as for baseline.



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Figure 41 Vertical beam pattern for VVS outer cell

Figure 42 Vertical beam pattern for VVS inner cell

Real city network topology with realistic site locations for Nantes (Figure 43) and Marseille (Figure 44

) have been used as a base for the simulations. In the first step separate UL and DL downtilts

optimization have been done as according to results presented in section Extended Downtilts Control

of this Chapter have significant impact on network performance. This was treated as baseline

scenario.



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Figure 43 Network topology used for simulations for VVS for 66 sites (Nantes)

Figure 44 Network topology used for simulations for VVS for 168 sites (Marseille)

In the next step analysis of SINR for 4 cases have been done. Results are presented in Table 6: SINR

values are generally comparable to baseline for bath cases of MIMO2x2 however VVS offers

improved values for the range of SINR 1-16 dB over 6 dB due to the reduced power emitted to the

cell and noise level is lower. As case of VVS4x2 uses additional MIMO channels the SINR values are

close to baseline (1-2dB lower than baseline). VS for case 2x2 has similar SINR values of baseline

which does not confirm the results presented in section for vertical sectorisation, where no MIMO

channel has been studied. However for case for VS4x2 the theoretically calculated SINR degradation



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is observed in this simulation as well: for SINR values in range -3 to 13 dB the difference exceeds

10 dB. On Table 6 two levels have been highlighted: -5 dB and -8 dB. The first one refers to the level

of baseline and 2x2MIMO (VS and VVS) results for 96-98% of users with SINR -5 dB or higher, the

second the same comparable level 97-99% but for -8dB SINR.

Table 6 Comparison of 2x2 MIMO vs 4x2 MIMO with VS and VVS for low SINR

The same results are presented in graphical way as CDF SINR function on Figure 45.

Figure 45 CDF SINR – VS and VVS (2x2 and 4x2)

Table 7 represents results of average throughputs in sector achieved in Nantes. Where definition of

sector stays as originally assigned to baseline configuration. For VVS stays the same (with virtual



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inner and outer beams) as for VS both new sectors: inner and outer throughputs are added and

throughput cell is calculated as sum to allow equal comparison to VVs and baseline.

Table 7 VVS throughput gain results in comparison to VS (2x2 and 4x2) -Nantes

DL Average sector throughput

Gain Average user throughput

Gain 5% percentile user throughput

Gain

Baseline 2x2

27.5Mbps - 1.5Mbps - 224kbps -

VS 2x2 35.9Mbps 30% 1.9Mbps 31% 245kbps 9.3% VS 4x2 39.4Mbps 43% 2.2Mbps 43% 268kbps 19.5% VVS 2x2 33.7Mbps 22% 1.8Mbps 22% 253kbps 13.1% VVS 4x2 36.7Mbps 33% 2.0Mbps 33% 325kbps 45.2% UL Average

sector throughput



Gain

Baseline 1x2

14.4Mbps - 607kbps - 46kbps -

VS 1x2 18.9Mbps 32% 785kbps 29% 70kbps 52% VS 1x4 22.5Mbps 56% 925kbps 52% 99kbps 115% VVS 1x2 17.6Mbps 22% 730kbps 20% 80kbps 74% VVS 1x4 21.4Mbps 49% 879kbps 45% 107kbps 132%

Table 8 presents results achieved in Marseille simulation case for DL and UL. For both cases Nantes

and Marseille VVS results are promising for cell edge where 5% user throughput gains are for DL 28-

45% (VVS4x2) and for UL: 66-132% (VVS4x2). Average gain throughput gains simulated on the same

platform with the same channel modeling, traffic model, antenna patterns, optimization process for

downtilting indicate significant difference in relation to network topology DL (38%) UL (50%).

Table 8 Throughput gain results – comparison VVS to VS (2x2 and 4x2) -Marseille

DL Average sector throughput



Gain

Baseline 2x2

11.7Mbps - 1.1Mbps - 225kbps -

VS 2x2 19.2Mbps 64% 1.7Mbps 57% 242kbps 7% VS 4x2 20.9Mbps 78% 1.8Mbps 71% 252kbps 12% VVS 2x2 15.9Mbps 36% 1.5Mbps 35% 264kbps 17% VVS 4x2 17.2Mbps 47% 1.6Mbps 46% 287kbps 28% UL Average

sector throughput



Gain

Baseline 1x2

8.4Mbps - 658kbps - 169kbps -

VS 1x2 10.6Mbps 25% 829kbps 26% 234kbps 39% VS 1x4 13.0Mbps 53% 1007kbps 53% 263kbps 56% VVS 1x2 9.8Mbps 16% 782kbps 19% 246kbps 46% VVS 1x4 12.3Mbps 44% 952kbps 45% 280kbps 66%



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This can be explained by different cell sizes as Marseille simulated network is bigger: larger number

of sites are located in suburban area and for Nantes ISD is lower than Marseille.

In order to further investigate the spread of gains additional simulations have been done strictly

comparing VS and VVS resource utilization for MIMO2x2 conditions for fixed Inter-Site Distance equal

to 500 m. Quantified load has been simulated starting with low 2Mbps increasing up to 18 Mbps per

cell.

Environment has been defined according to scenario 3GPP Case 1 (reference document 3GPP TR

36.814 V9.0.0) Test environment was defined as urban. Network layout - hexagonal grid with 7 cell

sites, 3/6 sectors per site => 21/42 sectors (for VVS and baseline/ VS).Carrier Frequency for

simulation was setup on 2000 MHz, bandwidth 10 MHz.

Further details of simulation setup: user simulations dropping randomly and uniformly over coverage

area. Users distribution 100% indoor in NLoS conditions (20dB loss). Number of users per cell was

based on FTP traffic model with file size 2 Mbytes lambda = 0.125 | 0.325 | 0.625 | 0.75 | 0.875 | 1.0

| 1.125 Max Download Duration = 32s.

The high throughput results achieved in simulation for Nantes were not confirmed in other

simulations. In controlled uniformly modeled environment for ISD=500 m and for Marseille case the

results are lower. As conclusion of above analysis a Marseille case provided more conservative

estimations in terms of throughput values but reference Marseille case results are below average,

which reflects with too high gain conclusions. Nantes case is too optimistic as throughput values (for

all scenarios) – the other simulations (not presented in this paper) do not confirm the availability of

such high throughputs. However gains conclusions are more conservative in Nantes and probably

more realistic as included in results of Marseille studies as well.

Finally the proposed conservative assumption (based on presented outputs) for VVS DL cell

throughput gain is 36% with MIMO2x2.

4.5 User specific tilt

Another beamforming technique that was recently revealed as patent No US2011/0103504 A1 [39] is

based on virtual vertical sectorisation formed in baseband using codebooks as set of potential beams

to be adapted for alternative beams. Beams are created as a superposition of pre-coding user data

that, as specified in [39], is automatically tailored to the user (however no specific method is

provided how this automatic tailoring is done). The general statement that each of the beam is used

by base station for transmitting separate pilot signal and mobile measures the two signals to

determine the phase shift between the signals does not provide an explanation how the method can

be realistically implemented in 3G or LTE technology. Further explanation and examples of the

antenna patterns are provided without any realistic simulations and indicate a high level concept of

the invention.

There general idea is based on 2 major options of codebook utilization for 2 port antenna and 4 port

antenna. The first one presented for hypothetical 12 –element uniform array spaced λ/2, one column

antenna allows to obtain (theoretically) down-tilted beam 2o and the second beam 10o both with



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vertical 9o HPBW. The option 2 with higher number of virtual antennas (4) used 4 layers of codebook

allow 16-virtual beams generation. As it has been assumed a 10 –element uniform array spaced

0.85λ, one column antenna can provide: down-tilted beam 0o and the second beam 6o both with

vertical 6o HPBW (this might be very interesting as in anechoic chamber tests indicate that achieving

vertical 6o HPBW with 10 elements array is not trivial). With some further tuning of pre-coding beams

parameters the more adequate downtilts were achieved based on proposed user specific tilt

method. Results for 2-port antenna have been presented on Figure 46 a portfolio of 3 beams with

tilts 10o, 14o, 18o are available for 2 antenna ports configuration.

Figure 46 Virtual beams created based on UST method (2 ports)

The beams are created based on code book specified in Table 9.

Table 9 Codebook for 2 antenna ports

Generally there are two different possibilities of providing phase shifting and final beamforming

techniques for UST. Figure 47 shows scenario with a beamforming technique performed mainly in

analog RF part where power amplifiers feed antenna elements that are controlled by baseband unit.

As an alternative solution specified in Figure 48 - separate transmission elements controlled

individually by baseband unit is proposed. Baseband digital signal processing per user increases with

the number of independent signals that are processed for each user. Beamforming with feeding each

element as independent antenna generally involve a large amount of baseband signal processing and

overhead resource.



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Figure 47 Plane beamforming with baseband unit control of 2 separate power amplifiers

Figure 48 Baseband beamforming with dedicated power amplifiers to each antenna element

The analyzed 3GPP case 1 coverage with a proposed downtilts: 10o, 14o, 18o Błąd! Nie można

odnaleźć źródła odwołania.are presented in Table 10 below.

Table 10 UST pre-coded beams – calculated range of coverage for 3GPP case 1

Calculated range of coverage of 3-beam UST

(antenna installed on 32m above terrain; 500m site separation)

Beam A

(-10o: 8o mechanical downtilt + 2o electrical)

-3dB upper edge 228m

center of the beam 181m

-3dB lower edge 151m

Beam B

(-14o: 8o mechanical downtilt + 4o electrical)



-3dB lower edge 112m

Beam C

(-18o: 8o mechanical downtilt + 10o el.)



-3dB lower edge 88m

Number of uncertainties and unclear issues have been discussed with author of the concept Zhengxiang Ma in Munich (2012) – questions are still pending. No clear answers have been delivered.



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Based on preliminary result UST concept to is not very promising in comparison to 4x4 MIMO technique. UST as is based on adopting standard codebook does not allow MIMO technique implementation. The simulated results of those techniques should allow achieving throughput c.a. 6.5 -7.9% gain in comparison to 2x2MIMO (standard site configuration) – results are listed in Table 11.

Table 11 Throughput results for UST and MIMO

Throughput*

Technique

User Specific Tilt (2

antenna port/ 4

antenna port)

2x2MIMO 4x2MIMO

Mbps 22.8 / 23.1 21.4 24.5

*) for 10MHz bandwidth

4.6 Horizontal beam switching with VVS

This concept of combining horizontal dynamic sectorisation with vertical dynamic sectorisation was

evaluated in [38]. Similar to the idea is a concept presented in this thesis however is based on

combining horizontal beam-switching and VVS a realistic features simulated and measured

separately.

4.6.1 Principles of horizontal beam switching with VVS

The concept of beam steering / selection is based on Release 10 Cell Specific Indicators described in

VVS section. Adding horizontal beam switching based on physical antenna dipoles directed to fixed

azimuth requires additional steering of 4 cross-polarity beams: 8 possible channels for 2x2MIMO.

There are 2 possible transmitting scenarios for common channels (CRS/PDCCH/PBCH):

1. Left module10 (1) combined inner + outer beam – VVS off

2. Right module (2) combined inner + outer beam – VVS off

There are 4 possible transmitting scenarios for traffic channels (PDSCH):

1. Left module inner cell

2. Left module inner outer

3. Right module inner cell

4. Right module inner outer

The algorithm for steering horizontal beam-switching and VVS is based on CRS (Rel. 8) antenna port

{0..3} were ports {0,1} are assigned to module 1 and ports {2,3} to module 2. That allows for Release

8 users be served by the system with 2x2MIMO. No 4x4MIMO is possible for common channels.

A periodical switching algorithm for common channels has been used. Signals are transmitted

periodically though module 1 and module 2, switching time might be a subject of adjustment by SON

10

Concept of modules is described in Chapter 6 where schematic diagram of proposed antenna model is presented



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however preset value is proposed as 10 ms which will be in line with receiving CQI reports from UE’s

(as specified further). The common channel transmitted though module with typical 65o horizontal

HPBW guarantee that signaling will be provided as in baseline scenario. Adding switching

functionality allows cell edge users benefit from higher directional gain in 50% of the time. Further

impact on coverage has not been investigated as major focus of the thesis is on DL throughput gain.

Common channel performance will not suffer due to proposed algorithm. In case of implementation

problems with intercell interference the switching algorithm might be turn off as not critical

functionality for overall proposed concept.

As CRS with common channels are transmitted in combined inner outer beam per module, CSI are allocated to inner and outer beam with expanded logic to 8 ports Figure 38, Figure 39:

set ”i”: CRS: only 2x2MIMO as described above

set “jM1”: CSI-RS PDSCH is mapped on RE for inner cell:

antenna port {15} +45o polarization 2x2MIMO

antenna port {16} -45o polarization 2x2MIMO

antenna port {7} left RE reserved for CSI-RS +45o polarization option for 4x2MIMO

antenna port {8} left RE reserved for CSI-RS -45o polarization option for 4x2MIMO

set ”kM1”: CSI-RS PDSCH is mapped on RE for outer cell



antenna port {9} left RE reserved for CSI-RS +45o polarization option for 4x2MIMO

antenna port {10} left RE reserved for CSI-RS Figure 49 -45o polarization option for 4x2MIMO

set “jM2”: CSI-RS PDSCH is mapped on RE for inner cell



antenna port {7} right RE reserved for CSI-RS +45o polarization option for 4x2MIMO

antenna port {8} right RE reserved for CSI-RS Figure 49 -45o polarization option for 4x2MIMO

set ”kM2”: CSI-RS: PDSCH is mapped on RE for outer cell



antenna port {9} right RE reserved for CSI-RS +45o polarization option for 4x2MIMO

antenna port {10} right RE reserved for CSI-RS -45o polarization option for 4x2MIMO

As described above for 4x2MIMO ports {7..10 } were used with sharing the assigned by standard 2RE to different paths: left RE to left module M1 and right RE to right module M2. This proposal is not standardized due to that fact alternative solution for 4x2MIMO is proposed with common inner beam. Options with 4x2MIMO were not simulated and it is not possible at current stage to conclude which option is more adequate.



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Figure 49 Allocation of CSI for ports {7..10} for normal cyclic prefix 3GPP 136.211

ALTERNATIVE setting for PDSCH for 4x2MIMO with combined virtual inner cell:

set ”kM1”: CSI-RS PDSCH is mapped on RE for outer cell

antenna port {15} +45o polarization (first column module 1)

antenna port {16} -45o polarization (first column module 1)

antenna port {17} +45o polarization (second column module 1)

antenna port {18} -45o polarization (second column module 1)

set “jM1+ jM2”: CSI-RS PDSCH is mapped on RE for inner cell

antenna port {7} +45o polarization (first column module 1 and 2)

antenna port {8} -45o polarization (first column module1 and 2)

antenna port {9} +45o polarization (second column module 1 and 2)

antenna port {10} -45o polarization (second column module 1 and 2)

set ”kM2”: CSI-RS: PDSCH is mapped on RE for outer cell

antenna port {19} +45o polarization (first column module 2)

antenna port {20} -45o polarization (first column module 2)

antenna port {21} +45o polarization (second column module 2)

antenna port {22} -45o polarization (second column module 2) Ports {7..10} are allocated to inner cell because there is only for normal prefix cycle standard assignment of CSI –RS provided and delay for inner cell should be lower than in outer where extended cycle prefix is also allowed. Combined inner cell between module 1 and module 2 are justified by low relatively low number of users in inner dell due to limited coverage. PDSCH transmitting path is selected based on CQI parameter delivered by UE’s. UE Release 10 are scheduled to report CQI every 10ms: report r for inner beam module 1, report r+1 for outer beam module 1, report r+2 for inner beam module 2, report r+3 for outer beam module 2. Report is made of CQI, where CQI is one value in the set {0,1,2,3,…,14,15} (4 bits), higher refers to the better quality of the beam. Based on provided information BS can build a “data base” for 4 beams and up-date it as report coming; this integration with simulation results trigger allocation of beam to the UE. Generally selected beam is the one with the highest CQI value.



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4.6.2 Simulations of VVS combined with horizontal beam-switching

The research11 presented in [68] is mainly concentrated on vertical dimension of dynamic beam-

steering but also has been investigated simulations of horizontal and vertical beam steering.

Interested results have been achieved for combined together techniques. Simulations were done for

antenna array (4 elements half-wavelength spacing).

In case of proposed in thesis antenna model with improved antenna patterns compared to

traditional antenna array with horizontal beam-steering (due to the reduction of sidelobe effect that

as presented in detail for V6S gain analysis) improvement of 10 dB SINR is achievable.

Below the argumentation is presented that proves the concept of beam-switching brings better

results than proposed antenna array adaptive solution with 70o HBPW:

In the section for V6S simulations it has been presented results for range of horizontal beamforming

limitations. The antenna array pattern distortion limiting the range of horizontal adaptation to ±15o,

(for assumed in [68] 70o horizontal HPBW). Increasing range of horizontal beam-steering is possible if

HPBW is more narrow. However due to multipath propagation that caused azimuth signal spread – in

order to receive majority of the scattered signal energy the horizontal antenna pattern cannot be too

narrow.

Figure 50 Horizontal angle spread – average 10o

Horizontal angle spread (AS) based on measurement results presented in Table 15 and based on

analysis shown on Figure 50 is 10o for multipath urban environment. According the AS measurements

the HBPW should be at least 20o to fit to all measured environments. The 65o horizontal HPBW (as

most typical) is optimal for majority of environments to capture main and reflected beams.

Below 2 scenarios are considered assuming main beam directions and neglecting (due to simplicity

for this analysis) the signal angle spread:

1. Scenario 1: direction 0o (orthogonal to antenna array= 26.6o to module 1 or 2)

11

Research under funding from the European Commission’s seventh framework program FP7-ICT-2009 under grant agreement n° 247223 also referred to as ARTIST4G.



__________________________________________________________________________________ PAGE 73

2. Scenario 2: direction ±15o (edge of flexibility of antenna array = 11.6o to module 1 or 2).

In scenario 1 the main signal path is coming from the direction of the beam azimuth; the maximum

loss comparable to antenna array is 1.95 dB, for scenario 2 loss is 0.38 dB according to the presented

in Table 12 directions 12o and 27o of modeled antenna (values are part of the simulation results

presented in Table 23 in Appendix B).

Table 12 Gain loss due to inefficiency of horizontal beam-switching

LOCATION directivity in dB

THETA PHI vert. horiz.

90.00 0.00 16.2362 16.2362

90.00 12.00 15.8530 15.8530

90.00 27.00 14.2817 14.2817

For scenario 1: Calculated loss is observed only for directions when antenna array is directed towards

main beam without adaptation as beam-switching azimuth stays on predefined direction. The range

of the loss is 30o in 120o sector. For the rest 90o of 120o sector the beam-switching technique

provides higher antenna gain then adaptive array.

For scenario 2 antenna array is affected by the loss of sidelobes and array beam gain is significantly

decreased; this pointing 15o range as an average point where gain for beam-switching and beam-

steering are equal.

An alternative solution for beam-switching is presented: a beam-steering with adaptive antenna

pattern. Concept is based on changing antenna horizontal HPBW as need of horizontal shift is

appearing. As non-adaptive orthogonal beam has 50o horizontal HPBW, for horizontal shift is used

beam reduced to 30o HPBW, details in Appendix G. The concept allows double the range of

horizontal beam adaptation to ±30o and reduces sidelobes to -15dB. The results are presented in

Table 13 that has summarized values of gain losses for all directions in 120o sector in step of 5o

(symmetric sector is assumed).

Table 13 Modeled switch beam in comparison to adaptive array antenna pattern

azimuth direction -60 -55 -50 -45 -40 -35 -30 -25 -20 -15 -10 -5 0 [

o]

adaptive array

(estimated)

-10 -7,5 -5 -3 -2 -1 0 -1 -2 -0,9 -0,5 -0,2 0 dB

adaptive -30o (horizontal 30

o HPBW) non-adaptive beam

beam-switching based on

model

-3,4 -2,4 -1,8 -1 -0,5 -0,3 -0,1 0 -0,1 -0,3 -0,5 -1 -2 dB

module 1 : horizontal 67o HPBW

comparison results -6,6 -5,1 -3,2 -2 -1,5 -0,7 0,1 -1 -1,9 -0,6 0 0,8 2 dB

Also in this case modeled antenna pattern provides better results than measured adaptive array for

2x45o of 120o sector.



__________________________________________________________________________________ PAGE 74

Modeled antenna has the same performance as horizontal beamforming or even better as impact of

antenna pattern is analyzed. The SINR improvement for modeled antenna is at least on the level of

simulated in [38] results for horizontal and vertical steering technique which is presented on Figure

51.

Figure 51 SINR results for horizontal and vertical steering techniques [68]

The two solid lines depict the case with the static horizontal sector pattern. The offset between the

black and the grey line is the gain, approximately 2 dB, achieved by direct main lobe steering in

vertical direction. The two dashed lines represent the combination with horizontal beam steering. A

gain of about 10 dB from the horizontal beam steering is obtained. The gain originating from vertical

dynamic beam steering almost persists, i.e. the two effects are additive. This final result indicates

that the gain due to vertical beam steering can be achieved almost fully in addition to the gains of

other performance enhancing techniques. Adding studied in previous sections results of simulations

for V6S and VVS the expected throughput gain for modeled antenna is at least 40% mainly due to

horizontal beam-switching and additional gain up to 30% as traffic is located close to the cell center.

Effect of positive VVS impact is also observed on Figure 51 for 10% of users SINR values 30-50dB.

This proves significant 40-70% throughput gain to be achieved base on switching-beam control

mechanism with modeled antenna if the physical antenna can keep assumed parameters.



__________________________________________________________________________________ PAGE 75

Chapter 5: Channel modeling and field measurements results As in previous chapters studies were concentrated on most suitable techniques for optimum antenna

structrure in this chapter antenna pattern parameters will be analysied. An attempt of finding a

range of horizontal HPBW and vertical HPBW for VVS and horizontal beam-switching is taken. The

most typical channel for urban evironment definition is introduced based on 15 available in litreature

measurements and 2 dedicated campaingns described in this chapter.

Starting the analysis of channel modeling an existing 2D model has been examined.

5.1 The existing 2D channel modelling and its constraints

The 2D spatial channel model is modeling the radio propagation environment by a number of

clusters of scatters. The cluster statistics and array orientations are varied in each drop. A cluster

corresponds to a double directional: Angle of Arrival (AOA) and Angle od Departure (AOD) angles on

the MS-BS line. Separate path and each path consists of a number of subpaths that are spatially

distributed with some angle spread. The AOA and AOD angles of each path/subpath are described

only by the azimuth angles in the XY plane and elevation angles are not considered. 2D spatial

channel modeling is shown in Figure 52 and the corresponding channel matrix (in NLOS and polarized

case and linear array assumed) is expressed by equation below [35]:

M

mtiii

MS

nm

h

MSu

MS

nm

v

MSu

jj

n

j

n

j

BS

nm

h

BSs

BS

nm

v

BSs

SFnnsu

MSnm

MSu

MSnm

BSs

BSnm

hhnm

vhnm

hvnm

vvnm

eee

χ

χ

eer

ere

χ

χ

M

Pth

1

,

)(

,

,

)(

,

2

1

,

)(

,

,

)(

,

,,

,,,

),(,

),(,

),(,

),(,

)(

)(

)(

)(

)(

vkrkrk

k

k

k

k

(35)

where )()(i

j , i=v or h, j = BS or UE, denotes the antenna response for the i-pol component at the

azimuth angle θ The term ),(

,

yx

mn denotes the phase offset between x-pol component at BS and y-pol

component at UE.

BS

AoDn,

, ,n m AoD

AoDmn ,,

BS

N

N Cluster n

AoAmn ,,

, ,n m AoA

,n AoA

MS

MS

v

BS array

MS array

BS array

MS direction of travel

MS array

Subpath m

v

Figure 52 2D channel modeling based on [35]



__________________________________________________________________________________ PAGE 76

2D spatial channel modeling is a simplified approach for modeling practical propagation under the

following assumptions:

1. The cell radius is relatively large such that statistically most of the users are distributed with very

small elevation angles, which can approximately be ignored in the channel modeling for

simplicity.

2. The antenna array geometry is mainly focused on the one dimensional linear arrays, which can only resolve the azimuth angles and the not the elevation angles.

5.2 3D channel modelling

In 3D channel modeling, the departure and arrival angles have to be modeled using not only the

azimuth angle in XY-plane, but also the elevation angle with respect to the Z axis. A spherical

coordinate system for 3D channel model is shown in Figure 53. In this case, the 2D channel modeling

can be extended to the 3D case, as shown below:

M

mtiii

MS

nm

h

MSu

MS

nm

v

MSu

jj

n

j

n

j

BS

nm

h

BSs

BS

nm

v

BSs

SFnnsu

MSnm

MSu

MSnm

BSs

BSnm

hhnm

vhnm

hvnm

vvnm

eee

χ

χ

eer

ere

χ

χ

M

Pth

1

,

)(

,

,

)(

,

2

1

,

)(

,

,

)(

,

,,

,,,

),(,

),(,

),(,

),(,

)(

)(

)(

)(

)(

vkrkrk

k

k

k

k

(36)

where:

cos

sinsin

cossin2

k

Figure 53 3D channel modeling based on [35]

The variable r ( BS

sr or MS

ur ) is the vector denoting the position of antenna element with respect to the

reference point in 3D space. The operation “ ” represents the dot product (or scalar product) of the



__________________________________________________________________________________ PAGE 77

two vectors. In 3D channel modeling the phase shifts between different BS (UE) antennas are

dependent on the projections of the BS (UE) antenna element position vectors onto the departure

(arrival) wave direction vectors in 3D space. The antenna element position vectors are determined by

the applied antenna array geometry.

3D channel modeling was considered in the WINNER II and WINNER+ projects. In the WINNER phase

II channel model. 3D spatial channel modeling methods were considered in order to generate the

elevation arrival angle and elevation departure angle for each cluster. However, the definition of the

elevation related parameters are only for limited scenarios. In the WINNER phase II channel model

implementation (WIM2_3D_ant_ver064_220908 on the WINNER-II website), only the 3D antenna

array geometry was considered, instead of the 3D modeling of AODs and AOAs. In the WINNER+

channel model defined in [33] the 3D channel modeling was considered more fully. The elevation

parameters for 5 scenarios, including indoor, urban macro, urban micro, suburban macro and

outdoor-to-indoor were provided. 3D channel model is recommended by 3GPP to be applied when

there is a need for realistic evaluations. The model defines the angular spread in the vertical direction

as well as the horizontal direction, recognizing that the angular spreads in the horizontal and vertical

directions.

5.2.1 Theoretical channel model analysis

According to presented above recommendation a 3D modeling analysis need to be done to properly

simulated complexity of signal propagation in urban environment. In order to do that tapped-delay-

line models [79] and MIMO models: spatial channel model. ITU and Winner have been considered.

For the purpose of comparison the different models a spherical coordinate system has been used

presented in Chapter 3 on Figure 11 page 31 and following definitions are introduced:

Signal Pi is represented by τi (delay) and azimuth φBS and φMS (on BS and MS side) elevation angles θBS

i θMS accordingly. Azimuth spread (AS) is defined as follow:

(37)

where:

, and (38)

For AS(Δ) modification is added Δ=1..2π to ensure that only main paths in horizontal plane are taken into account, narrowing area of AS investigation to 1rad angle (57.3o) allow obtaining realistic outputs adequate to cellular environment

Delay spread (DS) has been defined by:

and (39)



__________________________________________________________________________________ PAGE 78

In Table 1412 the outputs for AS and DS for different models are presented, where AS-BS is the

azimuth spread calculated for the perspective of BS (uplink) and AS-MS from the perspective of MS

(downlink)

Table 14 DS and AS parameters for different channel models

Model DS (μs) AS-BS (°) AS-MS (°)

VA 0,37

PA 0,045

eVA 0,357

ePA 0,045

Winner C2 0,23 8,5 52,5

Winner C3 0,63 17 55

Winner B1 0,076 15 35

Winner B2 0,48 33 55

SCM Mikro 0,25 19 70

SCM Makro 0,65 15 70

ITU UMi 0,13 26 69

ITU UMa 0,365 26 74

Further details have been delivered in [75].

The aim of this research is provide solution and model of an antenna for BS according to Table 14 –

the desired theoretical goal for azimuth spread is below 33o .

5.2.2 Azimuth and elevetion sperad tests

For 3D channel modeling not only azimuth spread but also elevation spread need to be obtained. In

order to gather a realistic field data a test report has been studied. The testbed have been prepared

by Ericsson R&D and results have been published13 in [72]. The campaign comprising 10 non-line-of-

sight outdoor user equipment locations at distances up to 300 m from the BS location has been

performed at 5.25 GHz using 200 MHz bandwidth. Locations were selected as shown on Figure 54.

12

Calculation prepared by Orange Labs France(Jean-Marc Conrat) 13

Published April 16 2013: Journal Conference Papers at http://www.ericsson.com/thecompany/our_publications



__________________________________________________________________________________ PAGE 79

Figure 54 Measuring locations in urban environment for 3D channel modeling

A schematic drawing of the measurement set-up and a photograph of the scenario are shown on

Figure 55.

Figure 55 Schematic of measurement setup for testbed

At the BS a directional patch antenna with 7 dBi gain (90° beam width) and vertical polarization was

used. A virtual planar array of 10x25 elements, with 2 cm (0.35 λ) spacing was formed by means of an

antenna positioning system based on electro mechanical actuators providing spatial accuracy better

than 0.1 mm. In the user equipment end an ordinary vertical dipole antenna was used. The channel

was measured over 200 MHz bandwidth, using an Agilent E8358A vector network analyzer (VNA).

This measurement technique requires that both antennas are connected to the VNA with RF cables.

The typical loss for ordinary coaxial measurement cables is at the order of one dB per meter. In order

to allow large Tx-Rx antenna separations the RF signal was transmitted over an optical multimode

fiber using RF-to-opto and opto-to-RF converters. The results of RSSI combined for all 10 locations of

UE are presented on Figure 56.



__________________________________________________________________________________ PAGE 80

Figure 56 Aggregate directional spectra for all 10 UEs locations

Results of measurements for points 1..10 are combined into Figure 57 where typical 6 paths

(scattered group of signals) have been presented. The azimuths are scattered widely as azimuth

spread is for a single group is not bigger than 20o. Elevation observed in measurements are in range

(-1..-5o) mainly due to diffraction on edge of the building and non-LOS conditions.

Figure 57 Azimuth and elevation main paths directions

On Figure 58 14 is presented the elevation values in relation to the normalized distance BS-MS. The

elevation spread increases with distance however the value of 4o is not exceeded – this could be a

good target for limit of narrowing HPBW in vertical plane.

14 The various colors of curves correspond to different standard deviations of the estimation errors of elevation

angle (not relevant to main analysis of azimuth and elevation spreads



__________________________________________________________________________________ PAGE 81

Figure 58 Mean values for elevation (upper) and elevation spread in function of UE distance from BS

The another important conclusion for adaptive antenna techniques of this test case is that in the

measured specific urban environment vertical sectorisation might create the observed on Figure 115,

page 146 – discontinuous coverage of inner and outer beam if hypothetical edge of inner and outer

cell will be assumed for -6o elevation angle. VVS in such case is much more adequate with proposed

earlier algorithms will not cause handover increase.

Additionally particular case of UE location #1 and UE location #7 has been analyzed – results of

measurements presented on Figure 59 (green dot represents UE position in elevation plane – non-

LOS).

Figure 59 Results of for UE1 and UE7 locations of azimuth and elevations spreads

Even if mean of the main path of azimuth spread can be limited to c.a. 20o - as typical value observed

for UE#1 - in some location with high reflection (UE#7) the spread of reflected signals with strength



__________________________________________________________________________________ PAGE 82

lower by -10dB..-15dB have azimuth spread c.a. 50o. This might be not typical but horizontal HPBW

narrowing need to be carefully analyzed for adaptive antenna.

Further analysis of different scenario have been done to precisely answer the question of most desire

antenna parameters (vertical HPBW and horizontal HPBW) suitable for beam-switching technique

combined with VVS. For realistic dense urban scenario (detail assumptions of the simulation

parameters are unknown15) elevation spread (ES-BS) values have been collected for 13 points located

in main beam of simulated sector as presented on Figure 60. Statistics obtained for “canyon street”

environment are provided in conditions where there is much higher possibility to serve the traffic

located close to the site and use a wider range of possible elevation direction of arrivals.

Figure 60 Realistic elevation spread simulation for 13 canyon-street locations

The range of downtilts are analyzed in details in Chapter 4 in section of Extended Downtilts and are

presented on Figure 25, page 43 – the expected values are up to 18o. For simulation done for

elevation spread a fixed value of downtilt is used (optimized for commercial 3G network), however

the maximum values of spread are as high as 9o – taking this into account, the vertical HPBW should

cover the expected elevation spread. The simulated values are not in line to the high expected range

of downtilts (in measured environment only up to 8o and also it is not in line with the expected

elevation spread – for measured environment only 4o

Due to multipath propagation the average elevation spread is c.a. 6o as presented on Figure 61,

choosing more narrow vertical HPBW need to be carefully considered as not adequate to all cases.

As above results still leaving quite wide range of uncertainty further analysis are proposed to cross

checking the mid-step conclusions and further investigate the 3D channel molding subject.

15

Simulations provided by Huawei as inputs for 3D channel modeling.



__________________________________________________________________________________ PAGE 83

Figure 61 Elevation spread values obtained for canyon site configuration

Measurement campaigns have been done in Paris area by Orange Group which results are

synthetized in [46], [61], [75]. The tests aim is to define typical values for AS and DS observed form

BS for UL channel. The 450 measuring data sets are prepared for analysis to allow gather relevant

statistical data. The carrier frequency used in tests was set up on 2.2 GHz as mid frequency and the

analyzed bandwidth was 10 MHz. In the recent test campaign an enhanced by bi-polar antenna was

used with a bandwidth 62.5MHz [61]; however no significant impact on results was observed. The

measuring dataset is defined as a result of 50 consecutive snapshots collected by MS antenna

mounted on the roof of the vehicle Figure 62. Bi-polar dipole antenna was used at the transmitter

and was located on the roof of the car.

Figure 62 MS antenna used for measurements

The mobile terminal vehicle was driven at a predetermined speed such that the snapshots were

collected each λ/3 distances. A section defines a virtual linear antenna array at the mobile and can be

considered as a 20x100 MIMO measurement point as one snapshot was a simultaneous

measurement of 10 bi-polar complex impulse responses transmitted by BS collected by virtual 50 bi-

polar antennas (separated by λ/3). The UL channel measurements on existing 3G site locations were

done 9 dedicated sectors (3 physical locations with 3 sectors each). A bi-polar antenna array made up



__________________________________________________________________________________ PAGE 84

of 10 vertical sectorial sensors regularly spaced (5 cm = 0.36 λ) was used at BS. Collected

measurements are presented in 6 groups where 3 typical channels have been defined (Figure 63):

a) typical 1 (30% measuring sets) AS=4o and DS=175 ns

b) typical 2 (30% measuring sets) AS=5o and DS=240 ns

c) typical 3 (20% measuring sets) AS=16o and DS=300 ns

d) high DS (5% measuring sets) AS=6o and DS=550 ns

e) high BS-AS (5% measuring sets) AS=23o and DS=110 ns

f) low BS-AS (5% measuring sets) AS=0.5o and DS=170 ns.

0 0.2 0.4 0.6 0.80

5

10

15

20

25

30

35

40

Delay Spread (µs)

BS

- A

zim

uth

S

pre

ad

(°)

High DS

High BS-AS

Low BS-AS

Typical 1

Typical 3

Typical 2

Figure 63 Distribution of azimuth spread and delay spread 3 typical channels definition

In first set of measurements there was achived the azimuth spread at BS mean value (9.5°) and delay

spread mean value (0.250 μs). The majority of azimuth spreads, as was summarized in [46],are

ranged from 7° to 11°, and delay spreads are ranged from 0.1 μs to 1 μs. However the maxiumum

range of spread in some cases exeeds 30o. The horizontal 30-33o HPBW for adaptive pattern is

enough to capture the required energy defined as azimuth spread if ideal algoritm for azimuth

directivity is assumed. On Figure 64 realtion of AS to distance fom the center of the site was

presented. AS close to the site center (up to 100 m) is high (above 30o) as multipath propoagation

and close objects for scattering affect on channel. As distanse increase the average AS is getting

lower to reach its maximum values in range of 7o at the edge of cell (ISD750m). No dependency of DS

vs distance form the site was observed Figure 65.



__________________________________________________________________________________ PAGE 85

0 100 200 300 400 500 600 700 8000

5

10

15

20

25

30

35

40

Distance (m)

BS

-AS

(°)

Figure 64 Azimuth spread distribution (@BS) in function of MS distance from BS

0 100 200 300 400 500 600 700 8000

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Distance (m)

Dela

y S

pre

ad (

ns)

Figure 65 Delay spread distribution (@BS) in function of MS distance from BS

There were also analyses dependency of DS, AS and ES values for DL form MS perspective for DL

channel. Average AS 55o, ES 8o for DL channel were taken based on all 50 measuring points. Details of

archived results are presented on Figure 66.



__________________________________________________________________________________ PAGE 86

0 10 20 30 40 50 60 70 80 90 1000

2

4

6

8

10

12

14

16

18

20

Azimuth spread (°)

Ele

vation s

pead (

°)

Rx 3

Rx 1 Rx 4

LOS channels

Rx 2

Rx 5

Rx 7

Rx 6

Rx 8

Rx 9

Rx 10

0 10 20 30 40 50 60 70 80 90 1000

2

4

6

8

10

12

14

16

18

20

Azimuth spread (°)

Ele

vation s

pead (

°)

Rx 3

Rx 1 Rx 4

LOS channels

Rx 2

Rx 5

Rx 7

Rx 6

Rx 8

Rx 9

Rx 10

Figure 66 AS-MS and ES-MS distribution

Above results are important contribution for alternative work to MS adaptive antennas studies

however it also need to be considered for future heterogeneous networks where small cells layer are

installed below roof top and channels UL and DL can be studies as more symmetrical. In urban

environment when high percentage of the traffic is generated in building similar ES and AS might be

observed for macro sites as well. A good example of such situation is physical spread of received

signals and different DoA presented on photos documentation (Figure 67). Received paths (colored

according to signal strength) are gathered in particular MS locations where BS installation could be

considered (potential traffic hotspot). BS in both photo documented cases are located on the roof

top but as was noted for in-building MS traffic similar sources of the transmitted signal would be

generated.



__________________________________________________________________________________ PAGE 87

Figure 67 Received signals by MS in hotspots – potential locations of BS

Samples for UL channels energy spread at BS collected during the campaign are presented on Figure

68.

Taking above outputs for consideration finding vertical and horizontal HPBW typical values for urban

environment are not a trivial problem. A leverage need to be obtained between increasing antenna

gain and optimal size of HPBW. When gain is dropping (wider beam) probability of capturing majority

of signal energy increases. To narrow beam except high side lobes might be not optimal for multipath

environment with high elevation spread. To wide beam caused loss of dB’s in budget link and

efficiency decrease. The problem is well known in passive antennas but for adaptive decision on

optimal set of preselected beams need to be taken into account.

For further analysis consideration of typical 65o horizontal HPBW has been proposed and 11o vertical

HPBW with ability of overlapping inner and outer cell – according to VVS technique. For VS, vertical

beam need to be reduced to 6o or even 4o as is presented in Chapter 4 mainly due to overlapping and

interference level increase. The wider vertical beam is also an optimized parameter obtained in

feedback process of results from FEKO platform and antenna size and complexity requirements. The

11o vertical HPBW can be reduced also for VVS however such analysis are not provided in this

document.



__________________________________________________________________________________ PAGE 88

Figure 68 Energy spread in horizontal plane observed on BS in delay spread window

Other tests results available in litreature have been presented in Table 15.



__________________________________________________________________________________ PAGE 89

Table 15 Field measurement summary for DS, AS-BS, AS-MS, ES-BS, ES-MS

Location Band-width (MHz)

Carrier freq. (GHz)

DS (µs) AS-BS (°) ES-BS (°) AS-MS (°) ES-MS (°) Reference

Frankfurt 6 1.8 0.5 8 [45]

Paris 10 2.2 0.25 10 [46]

Norway 50 2.1 0.06 10 [47]

Sweden 150 1.8 0.11 8 [48]

Sweden 150 1.8 0.08 7 [49]

Stockholm 5 1.8 1 10 [50]

Bristol 20 1.9 0.44 10 [51]

Bristol 20 1.9 2.1 0.13 8 [52]

Bristol 20 1.9 2.1 0.3 74 [53]

Helsinki 60 5.3 8 2 52 8 [54]

Munich 120 5.3 0.5 10 60 [55]

Stockholm 200 5.25 0.25 20 80 20 [56]

Helsinki 100 5.3 0.13 48 [57]

Seoul 100 3.7 0.77 72 [58]

Beijing 100 2.35 0.21 65 [59]

Ilmenau 90 2.53 0.07 40 20 [60]

Paris 62.5 2.2 0.17 55 8 [61]

Dresden 100 2.53 0.13 5 33 15 [62]

Karlsruhe 120 2 0.2 11 [63]

Rotterdam Amsterdam

100 2.25 [0-0.6] [20-80]

[64], [65]

Stockholm - 1.8 16 72 [66]



__________________________________________________________________________________ PAGE 90



__________________________________________________________________________________ PAGE 91

Chapter 6: Adaptive antenna model As have been presented in earlier chapters there is high potential for antenna system that can

support horizontal beam-switching and VVS. The constrains discussed in channel modeling need to

met, paticulary horiznontal HPBW should be kept as in current 3 sector typical configurations as 65o.

Vertical HPBW to be kept above 6o due to vertical angle spread in urban environments.

Based on analysis provided in this thesis a proposal for antenna model is presented. Antenna is build

with 2 modules that splitting 120o cell on 2 parts. Both modules are integrated in one radome and

physically covered by plastic chasis meet the criteria of typical antenna size mounted for 1800 MHz

bands.As horizontal HPBW is around 67o a single module can cover 120o sector as in current typical

configurations. However the 2 modules are transmitting common channels in periodical way with

shifting antenna module every 10 ms. Module H1 and H2 angles are constructed in that way to keep -

3dB antenna pattern loss on the edge of 120o sector. In orthogonal cell azimuth c.a. 7o overlapping is

observed but the algorithm for primary option (without 4x2MIMO) does not consider common

transmission, so the impact of neighbour antenna pattern radiation was limited to passive elemrnt

impact in near-field.

Figure 69 General schematic of the antenna model

The proposed model which schemat is presented on Figure 69 is not supporting MIMO mode as

preliminary analysis were done for one polarisation only. After analysis of outputs that are presented

in this thesis further works are continuing and second model has been prepered as a base for

prototype.

Figure 70 Antenna model with X-polarity implementation allowing 8RxDiv



__________________________________________________________________________________ PAGE 92

The second model presented on Figure 70 supports 2x2MIMO with cross-polar dipols. For uplink the

8 individual paths can be used for building 8-way Rx Diversity: 2 modules with different horizontal

patterns, 2 vertical beams with different vertical patterns and finally ±45o polarity.

For further detail analysis model 1 is described as post porcessing of 2x2MIMO model is not finished.

As presented on Figure 71 during simulation processes run on FEKO platform 3D antenna beam

pattern has been build for quantified dowtilt values achived as phase shifting on dipoles feed in pairs.

Figure 71 Simulation of 3D antenna beam created by single module

Number of dipoles and spacing between dipoles were one of the optimization approaches to build a

desired vertical beam for modeled antenna. Capacity dependence on the number of elements in the

receive array for different element distances is presented on Figure 72 [1]. As the theoretical analysis

indicates the boundary of λ/4 spacing should be kept.

Figure 72 Theoretical capacity dependence vs antenna spacing model

This boundary is also known in literature as a threshold of impacting on antenna characteristic and

during modeling antenna dipole placing the distance was taken into account. Using the typical UHF



__________________________________________________________________________________ PAGE 93

antenna concept as a starting point antenna dimensions has been recalculated on central frequency

for f=1800MHz. On Figure 73 detail dimensions are presented.

Figure 73 Antenna model concept – single module with horizontal polarity

The wavelength for central frequency λ=166mm required following antenna element spacing:

72mm between symmetric blocks;

90mm between dipoles pairs that are feed by one PA from symmetric lines

109mm spacing between dipoles pairs to achieve desired vertical characteristic.

Dipoles spacing are above λ/4 this meet the criteria theoretically calculated.

Outputs of FEKO engine vertical and horizontal antenna characteristics for a single module for

downtilt 0 are presented on Figure 75 and Figure 74 respectively. The antenna characteristics are

created based on raw data outputs that are available in Appendix B: Table 23 Values of the scattered

electric field strength in the far field in H and Table 24 Values of the scattered electric field strength

in the far field in V.



__________________________________________________________________________________ PAGE 94

Figure 74 Vertical antenna patterns of single module

The HPBW (-3dB) values are as follow: Vertical HPBW is 11.83o, Horizontal HPBW is 66.66o. The

other parameters calculated based on FEKO outputs are:

1. First minimum in vertical plane for -13o suppression 24.85 dB

2. Upper side lobe (vertical plane) for +19o suppression 12.95 dB

3. Main beam gain 16.24 dB

4. Gain drop for 120o beam to 5.95 dB

5. Front-to-back radio (FtB) for 180o drops to the level of 17 dB

6. FtB truncation (without 90o and 270o as linear to antenna axis) calculated as suppression for

120o beam (estimated for 90-180o) is 21.2 dB. On Figure 76 has been presented the way of calculating truncation front to back ratio.

Antenna characteristics in this section are presented as normalized amplitude values (0.5 refers to -

6 dB) Further analysis for downtilts 5o, 10o, 15o, 20o were done. The downtilts were generated by

phase shifting of pair of dipoles. In order to properly simulate realistic antenna characteristics obtain

in far-field, a way of signal supply to each individual dipole needed to be presented.



__________________________________________________________________________________ PAGE 95

Figure 75 Horizontal antenna patterns of single module

Figure 76 Truncation for front-to-back ratio

Keeping a theoretical antenna with individual feeding of each dipole provides solution that required

16 power amplifiers; comparable to alternative currently available solution this increase dramatically

FEKO samples

(degrees)->

Gain (dB)



__________________________________________________________________________________ PAGE 96

the complexity of the model. In next step a solution with combining dipoles in pairs has been

simulated – the concept is presented on Figure 77.

Figure 77 Concept of signal supply to the individual dipoles for transmitter

As a result antenna patterns are still acceptable (fit into typical urban channel requirements) and

sidelobes suppression are also on the acceptable level. For further analysis a concept with 1:2

splitters is adopted, this allows reducing power amplifier number from 16 to 8 with no significant

impact on antenna parameters.

Table 16 Phase shifting used for VVS simulations

port/ dowtilts 5deg

5deg with splitter 1:2 10deg



20deg with splitter 1:2

1 0 0 0 0 0 0 0 0

2 17 34 51 68

3 34 34 68 68 102 102 136 136

4 51 102 153 204

5 68 68 136 136 204 204 272 272

6 85 170 255 340

7 102 102 204 204 306 306 48 48

8 119 238 357 116

A phase shift values used for simulating VVS technique realization on modeled antenna (values to be

used by vector k and j on Figure 78) are presented in Table 16.



__________________________________________________________________________________ PAGE 97

Figure 78 Vertical antenna pattern for downtilt -5o



As presented on Figure 78,Figure 79,Figure 80 the downtilts up to -15o are achievable without

causing a risk of interference problems. The upper side lobe stays above the horizon also values of

lower sidelobe for tilts 5 and 10 are acceptable as beams to be used for outer cell. Increasing

downtilts above 15o caused potential problems with upper sidelobe that start to be below horizon

and value of suppression decreases. That will cause negative impact on intercell interference and

high downtilts need to be avoided. For prototype implementation a mechanical downtilt of 7o will be

used to ensure proper functionality in desired level of downtilt flexibility discussed in earlier

chapters. Table 17 represents the configuration of possible VVS values for ISD500 and ISD1732.

Table 17 VVS values for modeled antenna with 7o mechanical downtilt

VVS parameters ISD500 UL ISD500 DL ISD1732 UL ISD1732 DL

Inner cell [o] 22 (7+15) 22 (7+15) 17 (7+10) 17(7+10)

Outer cell

(mechanical +

electrical) [o]

13 (7+6) 14 (7+7) 3 (7-4) 7 (7+0)

As presented in Chapter 4 in extended downtilts control section on Figure 27 downtilts are specified

according to optimal values (in case ISD1732m uptilt is used with mechanical 7o downtilt). Optimal



__________________________________________________________________________________ PAGE 98

values has been used for outer cell as inner cell has no “extension” of UL downtilts due to need of

keeping maximum separation in UL channel increasing diversity.

Higher mechanical downtilts are not recommended as shown on Figure 81 downtilts 14o might have

negative impact on antenna characteristic.

Figure 81 Vertical vs electrical downtilts coverage

With high downtilts back sidelobe is increasing and front-to back ratio starts to be reduced for

electrical downtilts above 15o for analyzed model. Results presented on Figure 82.

Figure 82 Increasing Front-to-Back ratio in high downtilts

This was the reason that for VVS predefined parameters setup no higher electrical downtilt than 15o

is used.

The final aspect of antenna the designed antenna model is dedicated to supply lines that need to fit

into achieved in simulation parameters. The analysis of impedance also allowed description of

expected band for the model. As central frequency is 1800MHz based on impedance |Z|, Im(Z), Re(Z)

and phase(Z) a band: 1710-1880MHz has been proposed where range of changes are relatively low.

For |Z| is 13Ω, phase(Z) the range of fluctuation is about 0.3o. Also the compensation of Im part

impedance should be possible as changes are within 5Ω range.



__________________________________________________________________________________ PAGE 99

Figure 83 Impedance |Z| 1710-1880 MHz band



__________________________________________________________________________________ PAGE 100

Figure 84 Impedance Im(Z) 1710-1880 MHz band



__________________________________________________________________________________ PAGE 101

Figure 85 Impedance Re(Z) 1710-1880 MHz band



__________________________________________________________________________________ PAGE 102

Figure 86 Impedance phase(Z) 1710-1880MHz band



__________________________________________________________________________________ PAGE 103

Chapter 7: Summary and conclusions

The simplified antenna concept for horizontal polarization has been modeled. The results of

the simulations indicated that the simplicity has no negative impact on expected range of

parameters. Additionally a model of the antenna concept with extension to 2x2MIMO (due

to implementation of cross-polar dipoles) has been simulated. Parameters are almost

identical to presented single polarity model. The MIMO ready model (Figure 70 Antenna model

with X-polarity implementation allowing 8RxDiv) is chosen for the base for prototype

preparation. The concept of the antenna with proposed in Thesis algorithm for beam-

switching and VVS technique can provide cell throughput gain in the level of 40% to 70%

Additionally based on other evaluated techniques it is expected that gain will be uniformly

distributed among cell. The level of gain depends on traffic location in cell however no

degradation of cell edge users is expected as for VS.

7.1 Suggestions for future work

A prototype of described antenna model is planned to be built by Wroclaw Orange Labs as prove of

the concept. Work on steering modules (BBU and integrated with antenna RRU) have not been

started but they are integral part of entire system where simulated and analyzed parameters can be

measured. The switch-beam VVS antenna model has been verified by Charted European Patent and

Trade Mark Attorneys, further patent works are on-going.

The further steps are now focused on building the prototype and measure the physical model in

controlled test environment. Planar (Figure 87) tests in anechoic chamber are planned with the

configuration presented on Figure 88. For far field measurements in La Turbie Orange Lab are

considered. The most challenging task is to deliver a RRU and BBU part of adaptive antenna to allow

adaptive algorithm implementation and control of vertical beamforming (VVS downtilts control) and

horizontal beam switching.

Figure 87 Options for near-field tests



__________________________________________________________________________________ PAGE 104

Figure 88 Anechoic chamber test configuration

Additionally presented results were compared to recently revealed tests results [88] and patent

submissions [89],[90] – conclusions presented in this Thesis are sustained.

7.2 Summary

Proposed in Thesis adaptive antenna model can bring capacity enhancement up to 70% using

combination of horizontal beam-switch and VVS. The theoretical analysis with additional field tests

done for individual techniques (VS, VVS, V6S) proves the ability of achieving the estimated cell

throughput gain. The capacity improvement algorithm proposed as an integral part of the solution

has been designed for LTE Rel.10 and is mainly dedicated to the urban area with heavy traffic load. In

order to verify the ability of the antenna model to meet criteria of 3D urban channel model a number

of trials results were used and analysis of those results were presented. On top of that dedicated

simulations were done to obtain additional data for observed phenonomenas. Finally comparison to

existing prototypes with adaptive horizontal beam steering were done. However there are number of

uncertainties:

1. There is no simulator found to run a complete concept of combined beam-switching and VVS

with the algorithm of CSI selection.

2. Antenna model presented in the Thesis is based on single horizontal dipoles array – one

column per module. To support 2x2MIMO cross-polar dipoles need to be used (simulations finished

not presented in the Thesis). To support 4x2MIMO a second column is required which will have

impact on physical size of the antenna and complexity increase.

3. Further studies on SON related function are required - dynamic control on currently

predefined downtilts setup for VVS can bring additional gains not examined in this paper.

4. Separate DL and UL downtilts can bring additional several dB gain as obtained in simulations

presented in paper – this phenomena is not adopted in current modeled antenna solution.

5. Vertical HPBW can be reduced up to 4o; during antenna modeling design attempts on

achieving narrower beam in vertical plane needed to be leverage by side lobe suppression level.

However increasing number of dipoles in column could improve the parameter.

6. One of the biggest challenges is horizontal HPBW – in the proposed model it stays as typical

value 66,7o. The channel model AS measurements indicate that going down with horizontal HPBW

with additional ability of adaptive steering could bring interesting solution. One of such proposal is a

prototype which antenna patterns have been presented in Appendix F. However as proved in Thesis

method of beam-switching can bring higher performance than forming beams in horizontal plane



__________________________________________________________________________________ PAGE 105

with relatively high side lobes and directivity loss. Narrowing beam in horizontal plane by using

antenna array on 2 columns of Kathrein 80010622 antenna (tests described in Appendix D) does not

provided expected results. Theoretical V6V realization is not an obvious implementation.

7. VVS simulations results are relatively more reliable as done for several platforms with

different terrain models and additionally checked by theoretical uniform traffic distribution

simulations. The obtained in simulations value of average of 36% gain have mitigated uncertainty

level. There might be expected a higher gains if utilization of virtual inner cell is higher due to traffic

allocation close to the center of the site.

8. It must be admitted that VVS has been not verified in field test as theoretical concept only.

Evaluation of “sites” technique has been done for VS, where 70% gain has been achieved. VS is

strongly traffic depended and dedicated to congested cells recommended only with SON related

feature implementation which was not examined in this Thesis.

Proposed antenna model with the proposal of algorithm for LTE Release 10 can provide between 40-

70% average cell through gain in DL.



__________________________________________________________________________________ PAGE 106



__________________________________________________________________________________ PAGE 107

Appendix A: Acronyms

AA Adaptive Array

ADC Analog-to-Digital Converter

AoA Angle-of-Arrival

AWGN Additive White Gaussian Noise

BBU Baseband Unit

BER Bit-Error-Rate

BS Base Station

BPSK Binary Phase Shift Keying

CCI Co-Channel Interference

CDF Cumulative Distribution Function

CDMA Code-Division Multiple Access

CIR Carrier-to-Interference Ratio

CSI-RS Channel State Information – Reference Signal

CoMP Coordinated Multiponit Processing

CPRI Common Public Radio Interface

CQI Chanel Quality Indicator

CRS Cell Reference Signal

DAC Digital-to-Analog Converter

DMI Direct Matrix Inversion

DM-RS UE-specific reference signals

DL Down Link channel form BS to UE

DoA Direction-of-Arrival

eICIC Enhanced Intercell Interference Coordination

ESPRIT Estimation of Signal Parameters via Rotational Invariance Techniques

ETSI European Telecommunications Standards Institute

FDD Frequency-Division Duplex

FDPS Frequency-Domain Packet Scheduler

FEKO FEldberechnung bei Körpern mit beliebiger Oberfläche – Field: computations involving

bodies of arbitrary shape

FEM Finite Element Method

FIR Finite Impulse Response

GMSK Gaussian Minimum Shift Keying

HPBW Half Power Beam Width

ICIC Intercell Interference Coordination

IRC Interference Rejection Combining

ISD Inter Cell Distance

ISI Inter-Symbol Interference

LA Link Adaptation Entity

LMS Least-Mean-Square Algorithm

LOS Line-of-Sight



__________________________________________________________________________________ PAGE 108

LTE Long Term Evolution

MAI Multiple Access Interference

MBSFN Mobile Broadcast Single Frequency Network

MCL Minimum Coupling Loss

MIMO Multiple Input - Multiple Output

MISO Multiple Output - Single Input

ML Maximum Likelihood

MLSE Maximum Likelihood Sequence Estimation

MMSE Minimum Mean-Square Error

MRC Maximum Ratio Combining

MLFMM Multilevel Fast Multipole Method

MoM Method of Moments

MSE Mean Square Error

MU Multi User

MU-MISO Multiple User with Multiple antenna composite Input at the base station and Single

antenna Output at each mobile

MUSIC MUltiple SIgnal Classification

MU-SIMO Multi User with Single antenna Input at each mobile and Multiple antenna Output at base

station

MV Minimum Variance

NLOS Non-Line Of Sight

OFDM Orthogonal Frequency-Division Multiplexing

PA Power Amplifier

PBCH Physical Broadcast CHannel

PCCC Parallel Concatenated Convolution Coding

PDSCH Physical Downlink Shared CHannel

PDCCH Physical Downlink Control CHannel

PMI Precoding Matrix Indicator

PUSCH Physical Uplink Shared Channel

PRB Physical Resource Block

PRS Positioning reference signals

PS Packet Scheduler

QAM Quadrature Amplitude Modulation

QoS Quality of Service

QPSK Quadrature Phase Shift Keying

RE Resource Element

RET Remote Elctric Tilt

RF Radio Frequency

RI Rank Indicator

RRH Radio Remote Head

RRM Radio Resource Management

RSSI Received Signal Strength Indicator

SC-FDMA Single Carrier Frequency Division Multiple Access



__________________________________________________________________________________ PAGE 109

SDMA Space-Division Multiple Access

SEP Surface Equivalence Principle

SFIR Spatial Filtering for Interference Reduction

SIMO Single Input - Multiple Output

SINR Signal-to-Noise-and-Interference Ratio

SISO Single Input - Single Output

SNR Signal-to-Noise Ratio

SON Seft Optimizing Network

SRS Sounding Reference Signals

ST Space Time

SU Single User

SU-MISO Single User with Multiple antenna Input at the base station and Single antenna Output at

the mobile

SU-SIMO Single User with Single antenna Input at mobile and Multiple antenna Output at base

station

TDD Time-Division Duplex

TDMA Time-Division Multiple Access

TDPS Time-Domain Packet Scheduler

TTI Transmission Time Interval

UE User Equipment

UMTS Universal Mobile Telecommunications System

UL Up Link channel form UE to BS

ULA Uniform Linear Array

UST User Specific Tilt

VEP Volume Equivalence Principle

VNA Vector Network Analyzer

VS Vertical Sectorisation

VVS Virtual Vertical Sectorisation

V6S Virtual 6-Sector

3GPP 3rd Generation Partnership Project



__________________________________________________________________________________ PAGE 110



__________________________________________________________________________________ PAGE 111

Appendix B: FEKO antenna data

Following data is mainly retrieve from FEKO Suite 5.4 as output of antenna simulations. Additional

comments and major conclusions are added.

FEKO Version 54.277 from 2008-07-07 (FEKO Suite 5.4) PREFEKO version 33.45-83 from 2008-07-07 BINARY Copyright (c) 1999-2008 EM Software & Systems-S.A. (Pty) Ltd Intel(R) MKL version 10.0 (build 080702.10) on Intel(R) Core(TM) 2 Duo Processor (1 thread) Computer: PC WIN32 MKL -- SRV-OLPRA-WRO Server 4.0, Enterprise Edition Service Pack 1 (Build 7601), Version 6.1.7601 Intel(R) Xeon(R) CPU X5570 @ 2.93GHz; GenuineIntel family 6 model 10 stepping 5 brand id 0 2 physical CPUs with a total of 16 processors found (multi-core CPUs with max. 8 cores per physical CPU) Date: 2013-04-04 14:18:14 File: EAT 402 X2 Memory: Limited to 2.000 GByte, reason 224 MD5 Check:7A48C6269DDA1F883E8D6E3946165CBC Number of cores found on this CPU: 8 (that many parallel processes may be run with your sequential FEKO licence) Surface of all triangles in m*m: 0.1178304 Length of the segments in m: 0.728

Table 18 Data for memory usage

Number of metallic triangles: 826

Number of metallic segments: 56

Number of metallic edges (MoM): 1190

Number of nodes between segments: 48

Number of connection points: 0

Number of basis funct. for MoM: 1238

Table 19 Data for dielectric media

internal relative relative conductivity tan(delta) tan(delta) wavelength mass density volume medium

index permittivity permeability in S/m (electric) (magnetic) in m in kg/m^3 in m^3

0 1.00000 1.00000 0.00000E+00 0.00000E+00 0.00000E+00 1.66551E-01 0.00000E+00 infinite 0

Table 20 Excitation by voltage source at segment

Name: VoltageSource1

Number of voltage source: N = 1

Frequency in Hz: FREQ = 1.80000E+09

Wavelength in m: LAMBDA = 1.66551E-01

Open circuit voltage in V: |U0| = 1.00000E+00

Phase in deg.: ARG(U0) = 0.00

Source at segment w. label: ULA = Dipol1Line1.Wire1.Port1

Absolute number of segment: UNR = 4

Location of the excit. in m: X = 5.38000E-02

Y = 0.00000E+00

Z = 3.60000E-02

Positive feed direction: X = 0.00000E+00

Y = 1.00000E+00

Z = 0.00000E+00










Y = 0.00000E+00

Z = 1.26000E-01




__________________________________________________________________________________ PAGE 112

Y = 1.00000E+00

Z = 0.00000E+00










Y = 0.00000E+00

Z = 2.35000E-01


Y = 1.00000E+00

Z = 0.00000E+00










Y = 0.00000E+00

Z = 3.25000E-01


Y = 1.00000E+00

Z = 0.00000E+00










Y = 0.00000E+00

Z = -3.60000E-02


Y = 1.00000E+00

Z = 0.00000E+00










Y = 0.00000E+00

Z = -1.26000E-01


Y = 1.00000E+00

Z = 0.00000E+00










Y = 0.00000E+00

Z = -2.35000E-01


Y = 1.00000E+00

Z = 0.00000E+00








__________________________________________________________________________________ PAGE 113





Y = 0.00000E+00

Z = -3.25000E-01


Y = 1.00000E+00

Z = 0.00000E+00

All segments and triangles are perfectly conducting

DATA FOR STORAGE OF THE MATRIX

Memory requirement for MoM matrix:1248 rows and 1238 columns = 1545024 complex numbers For the MoM matrix, a memory of 1545024 complex numbers is available (i.e. 11.788 MByte) Storing the matrix and solving the linear set of equations in main memory, a total memory of 12.165 MByte has been allocated dynamically

Table 21 Data of the voltage source No. 1- 8

DATA OF THE VOLTAGE SOURCE NO. 1

real part imag. part magn. phase

Current in A 7.1882E-03 3.8448E-03 8.1519E-03 28.14

Admitt. in A/V 7.1882E-03 3.8448E-03 8.1519E-03 28.14

Impedance in Ohm 1.0817E+02 -5.7857E+01 1.2267E+02 -28.14

Capacitance in F 1.5282E-12

Power in Watt: 3.59411E-03



Current in A 8.8701E-03 1.8971E-03 8.1519E-03 12.07

Admitt. in A/V 8.8701E-03 1.8971E-03 8.1519E-03 12.07






Current in A 9.2224E-03 2.0499E-03 9.4475E-03 12.53

Admitt. in A/V 9.2224E-03 2.0499E-03 9.4475E-03 12.53






Current in A 7.0680E-03 1.6296E-03 7.2535E-03 12.98

Admitt. in A/V 7.0680E-03 1.6296E-03 7.2535E-03 12.98






Current in A 7.1894E-03 3.8428E-03 8.1520E-03 28.12

Admitt. in A/V 7.1894E-03 3.8428E-03 8.1520E-03 28.12






Current in A 8.8699E-03 1.8984E-03 9.0708E-03 12.08

Admitt. in A/V 8.8699E-03 1.8984E-03 9.0708E-03 12.08






Current in A 9.2230E-03 2.0490E-03 9.4479E-03 12.53

Admitt. in A/V 9.2230E-03 2.0490E-03 9.4479E-03 12.53






Current in A 7.0693E-03 1.6351E-03 7.2559E-03 13.02

Admitt. in A/V 7.0693E-03 1.6351E-03 7.2559E-03 13.02




__________________________________________________________________________________ PAGE 114



Table 22 Summary of losses

Metallic elements: 0.0000E+00 W

Dielectric (surface equiv. princ.): 0.0000E+00 W

Dielectric (volume equiv. princ.): 0.0000E+00 W

Dielectric (FEM region): 0.0000E+00 W

Mismatch at feed: 0.0000E+00 W

Non-radiating networks: 0.0000E+00 W

Backward power at passive waveguide ports: 0.0000E+00 W

Sum of all losses: 0.0000E+00 W

Efficiency of the antenna: 100.0000 %

(based on a total active power: 3.2350E-02 W)

Table 23 Values of the scattered electric field strength in the far field in H

LOCATION ETHETA EPHI directivity in dB POLARISATION

THETA PHI magn. phase magn. phase vert. horiz. total axial r. angle direction

90.00 0.00 9.057E-04 -1.80 9.030E+00 4.58 -63.7374 16.2362 16.2362 0.0000 89.99 LEFT

90.00 1.00 8.695E-04 2.19 9.027E+00 4.59 -64.0921 16.2337 16.2337 0.0000 89.99 LINEAR

90.00 2.00 8.352E-04 6.50 9.019E+00 4.58 -64.4411 16.2257 16.2257 0.0000 89.99 LINEAR

90.00 3.00 8.035E-04 11.13 9.005E+00 4.57 -64.7777 16.2125 16.2125 0.0000 89.99 RIGHT

90.00 4.00 7.748E-04 16.09 8.986E+00 4.55 -65.0935 16.1939 16.1939 0.0000 90.00 RIGHT

90.00 5.00 7.497E-04 21.37 8.961E+00 4.52 -65.3794 16.1700 16.1700 0.0000 90.00 RIGHT

90.00 6.00 7.288E-04 26.96 8.931E+00 4.48 -65.6256 16.1408 16.1408 0.0000 90.00 RIGHT

90.00 7.00 7.124E-04 32.81 8.896E+00 4.43 -65.8226 16.1062 16.1062 0.0000 90.00 RIGHT

90.00 8.00 7.011E-04 38.86 8.855E+00 4.37 -65.9620 16.0662 16.0662 0.0000 90.00 RIGHT

90.00 9.00 6.950E-04 45.04 8.809E+00 4.30 -66.0377 16.0209 16.0209 0.0001 90.00 RIGHT

90.00 10.00 6.943E-04 51.26 8.757E+00 4.22 -66.0465 15.9703 15.9703 0.0001 90.00 RIGHT

90.00 11.00 6.989E-04 57.45 8.701E+00 4.12 -65.9891 15.9143 15.9143 0.0001 90.00 RIGHT

90.00 12.00 7.086E-04 63.50 8.640E+00 4.02 -65.8692 15.8530 15.8530 0.0001 90.00 RIGHT

90.00 13.00 7.231E-04 69.37 8.574E+00 3.91 -65.6938 15.7862 15.7862 0.0001 90.00 RIGHT

90.00 14.00 7.418E-04 74.99 8.503E+00 3.78 -65.4713 15.7141 15.7141 0.0001 90.00 RIGHT

90.00 15.00 7.644E-04 80.33 8.427E+00 3.65 -65.2113 15.6366 15.6366 0.0001 90.00 RIGHT

90.00 16.00 7.901E-04 85.37 8.347E+00 3.50 -64.9232 15.5538 15.5538 0.0001 90.00 RIGHT

90.00 17.00 8.186E-04 90.12 8.263E+00 3.34 -64.6154 15.4655 15.4655 0.0001 90.00 RIGHT

90.00 18.00 8.494E-04 94.58 8.174E+00 3.16 -64.2955 15.3718 15.3718 0.0001 90.00 RIGHT

90.00 19.00 8.818E-04 98.77 8.082E+00 2.98 -63.9697 15.2726 15.2726 0.0001 90.00 RIGHT

90.00 20.00 9.156E-04 102.70 7.985E+00 2.78 -63.6430 15.1680 15.1680 0.0001 90.00 RIGHT

90.00 21.00 9.504E-04 106.40 7.884E+00 2.56 -63.3194 15.0580 15.0580 0.0001 90.00 RIGHT

90.00 22.00 9.858E-04 109.89 7.780E+00 2.33 -63.0017 14.9424 14.9424 0.0001 90.00 RIGHT

90.00 23.00 1.022E-03 113.19 7.672E+00 2.09 -62.6920 14.8214 14.8214 0.0001 90.00 RIGHT

90.00 24.00 1.057E-03 116.31 7.561E+00 1.83 -62.3918 14.6948 14.6948 0.0001 90.00 RIGHT

90.00 25.00 1.093E-03 119.28 7.447E+00 1.56 -62.1022 14.5627 14.5627 0.0001 90.00 RIGHT

90.00 26.00 1.129E-03 122.11 7.330E+00 1.27 -61.8235 14.4250 14.4250 0.0001 90.00 RIGHT

90.00 27.00 1.164E-03 124.82 7.210E+00 0.96 -61.5563 14.2817 14.2817 0.0001 90.01 RIGHT

90.00 28.00 1.199E-03 127.42 7.088E+00 0.64 -61.3004 14.1327 14.1327 0.0001 90.01 RIGHT

90.00 29.00 1.233E-03 129.92 6.963E+00 0.30 -61.0557 13.9781 13.9781 0.0001 90.01 RIGHT

90.00 30.00 1.267E-03 132.32 6.835E+00 -0.06 -60.8221 13.8178 13.8178 0.0001 90.01 RIGHT

90.00 31.00 1.300E-03 134.65 6.706E+00 -0.43 -60.5992 13.6518 13.6518 0.0001 90.01 RIGHT

90.00 32.00 1.332E-03 136.90 6.574E+00 -0.83 -60.3867 13.4799 13.4799 0.0001 90.01 RIGHT

90.00 33.00 1.364E-03 139.08 6.441E+00 -1.24 -60.1840 13.3022 13.3022 0.0001 90.01 RIGHT

90.00 34.00 1.394E-03 141.20 6.307E+00 -1.68 -59.9908 13.1187 13.1187 0.0001 90.01 RIGHT

90.00 35.00 1.424E-03 143.26 6.171E+00 -2.13 -59.8066 12.9292 12.9292 0.0001 90.01 RIGHT

90.00 36.00 1.453E-03 145.26 6.033E+00 -2.61 -59.6310 12.7337 12.7337 0.0001 90.01 RIGHT

90.00 37.00 1.481E-03 147.22 5.895E+00 -3.10 -59.4635 12.5322 12.5322 0.0001 90.01 RIGHT

90.00 38.00 1.509E-03 149.12 5.756E+00 -3.62 -59.3036 12.3245 12.3245 0.0001 90.01 RIGHT

90.00 39.00 1.536E-03 150.98 5.616E+00 -4.15 -59.1510 12.1107 12.1107 0.0001 90.01 RIGHT

90.00 40.00 1.562E-03 152.79 5.475E+00 -4.72 -59.0053 11.8906 11.8906 0.0001 90.02 RIGHT

90.00 41.00 1.587E-03 154.56 5.334E+00 -5.30 -58.8661 11.6641 11.6641 0.0001 90.02 RIGHT

90.00 42.00 1.611E-03 156.29 5.193E+00 -5.90 -58.7330 11.4312 11.4312 0.0001 90.02 RIGHT

90.00 43.00 1.635E-03 157.98 5.052E+00 -6.53 -58.6056 11.1918 11.1918 0.0001 90.02 RIGHT

90.00 44.00 1.658E-03 159.62 4.911E+00 -7.19 -58.4838 10.9457 10.9457 0.0001 90.02 RIGHT

90.00 45.00 1.681E-03 161.23 4.770E+00 -7.87 -58.3671 10.6929 10.6929 0.0001 90.02 RIGHT

90.00 46.00 1.703E-03 162.80 4.629E+00 -8.57 -58.2554 10.4332 10.4332 0.0001 90.02 RIGHT

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90.00 210.00 1.570E-03 -49.28 3.981E-01 -1.78 -58.9601 -10.8769 -10.8768 0.0029 89.85 LEFT

90.00 211.00 1.562E-03 -49.57 4.446E-01 5.26 -59.0031 -9.9178 -9.9178 0.0029 89.88 LEFT

90.00 212.00 1.553E-03 -49.79 4.945E-01 10.98 -59.0554 -8.9944 -8.9944 0.0027 89.91 LEFT

90.00 213.00 1.542E-03 -49.94 5.462E-01 15.70 -59.1167 -8.1303 -8.1302 0.0026 89.93 LEFT

90.00 214.00 1.529E-03 -50.03 5.987E-01 19.67 -59.1865 -7.3335 -7.3335 0.0024 89.95 LEFT

90.00 215.00 1.516E-03 -50.04 6.511E-01 23.07 -59.2641 -6.6045 -6.6044 0.0022 89.96 LEFT

90.00 216.00 1.501E-03 -49.98 7.029E-01 26.03 -59.3492 -5.9400 -5.9400 0.0021 89.97 LEFT

90.00 217.00 1.485E-03 -49.85 7.535E-01 28.66 -59.4410 -5.3357 -5.3356 0.0019 89.98 LEFT

90.00 218.00 1.469E-03 -49.65 8.027E-01 31.03 -59.5389 -4.7867 -4.7867 0.0018 89.98 LEFT

90.00 219.00 1.451E-03 -49.37 8.500E-01 33.20 -59.6422 -4.2886 -4.2886 0.0017 89.99 LEFT

90.00 220.00 1.433E-03 -49.01 8.954E-01 35.21 -59.7503 -3.8371 -3.8371 0.0016 89.99 LEFT

90.00 221.00 1.415E-03 -48.58 9.385E-01 37.09 -59.8623 -3.4285 -3.4285 0.0015 89.99 LEFT

90.00 222.00 1.396E-03 -48.07 9.792E-01 38.87 -59.9773 -3.0594 -3.0594 0.0014 90.00 LEFT

90.00 223.00 1.378E-03 -47.48 1.017E+00 40.57 -60.0947 -2.7269 -2.7269 0.0014 90.00 LEFT

90.00 224.00 1.359E-03 -46.81 1.053E+00 42.20 -60.2133 -2.4285 -2.4285 0.0013 90.00 LEFT

90.00 225.00 1.340E-03 -46.07 1.086E+00 43.78 -60.3323 -2.1619 -2.1619 0.0012 90.00 LEFT

90.00 226.00 1.322E-03 -45.25 1.116E+00 45.32 -60.4508 -1.9250 -1.9250 0.0012 -90.00 LEFT

90.00 227.00 1.305E-03 -44.35 1.143E+00 46.83 -60.5676 -1.7163 -1.7163 0.0011 -90.00 LEFT

90.00 228.00 1.288E-03 -43.38 1.167E+00 48.31 -60.6817 -1.5342 -1.5342 0.0011 -90.00 LEFT

90.00 229.00 1.271E-03 -42.35 1.188E+00 49.78 -60.7923 -1.3773 -1.3773 0.0011 -90.00 LEFT

90.00 230.00 1.256E-03 -41.24 1.207E+00 51.23 -60.8982 -1.2445 -1.2445 0.0010 -90.00 LEFT

90.00 231.00 1.241E-03 -40.08 1.222E+00 52.67 -60.9985 -1.1348 -1.1348 0.0010 -90.00 LEFT

90.00 232.00 1.228E-03 -38.85 1.235E+00 54.11 -61.0922 -1.0474 -1.0474 0.0010 -90.00 LEFT

90.00 233.00 1.216E-03 -37.58 1.244E+00 55.54 -61.1787 -0.9814 -0.9814 0.0010 -90.00 LEFT

90.00 234.00 1.205E-03 -36.26 1.250E+00 56.98 -61.2570 -0.9363 -0.9362 0.0010 -90.00 LEFT

90.00 235.00 1.195E-03 -34.90 1.254E+00 58.41 -61.3266 -0.9114 -0.9114 0.0010 -90.00 LEFT

90.00 236.00 1.187E-03 -33.52 1.255E+00 59.85 -61.3869 -0.9063 -0.9063 0.0009 -90.00 LEFT

90.00 237.00 1.180E-03 -32.11 1.253E+00 61.30 -61.4377 -0.9208 -0.9208 0.0009 -90.00 LEFT

90.00 238.00 1.175E-03 -30.69 1.248E+00 62.76 -61.4786 -0.9544 -0.9544 0.0009 -90.00 LEFT

90.00 239.00 1.171E-03 -29.26 1.240E+00 64.22 -61.5097 -1.0071 -1.0071 0.0009 -90.00 LEFT

90.00 240.00 1.168E-03 -27.84 1.230E+00 65.69 -61.5310 -1.0788 -1.0788 0.0009 -90.00 LEFT

90.00 241.00 1.166E-03 -26.42 1.217E+00 67.18 -61.5428 -1.1694 -1.1694 0.0010 -90.00 LEFT

90.00 242.00 1.166E-03 -25.03 1.202E+00 68.67 -61.5454 -1.2792 -1.2792 0.0010 -90.00 LEFT

90.00 243.00 1.167E-03 -23.66 1.184E+00 70.18 -61.5393 -1.4082 -1.4082 0.0010 -90.00 LEFT

90.00 244.00 1.168E-03 -22.32 1.164E+00 71.69 -61.5252 -1.5568 -1.5568 0.0010 -90.00 LEFT

90.00 245.00 1.171E-03 -21.02 1.142E+00 73.22 -61.5036 -1.7256 -1.7255 0.0010 -90.00 LEFT

90.00 246.00 1.175E-03 -19.76 1.117E+00 74.77 -61.4755 -1.9149 -1.9149 0.0010 -90.00 LEFT

90.00 247.00 1.180E-03 -18.55 1.090E+00 76.32 -61.4415 -2.1257 -2.1257 0.0011 -89.99 LEFT

90.00 248.00 1.185E-03 -17.39 1.062E+00 77.89 -61.4025 -2.3587 -2.3587 0.0011 -89.99 LEFT

90.00 249.00 1.191E-03 -16.28 1.031E+00 79.47 -61.3593 -2.6152 -2.6152 0.0011 -89.99 LEFT

90.00 250.00 1.197E-03 -15.22 9.978E-01 81.06 -61.3127 -2.8964 -2.8964 0.0012 -89.99 LEFT

90.00 251.00 1.204E-03 -14.22 9.631E-01 82.67 -61.2636 -3.2041 -3.2041 0.0012 -89.99 LEFT

90.00 252.00 1.211E-03 -13.28 9.265E-01 84.28 -61.2126 -3.5401 -3.5401 0.0013 -89.99 LEFT

90.00 253.00 1.219E-03 -12.40 8.882E-01 85.91 -61.1606 -3.9070 -3.9070 0.0014 -89.99 LEFT

90.00 254.00 1.226E-03 -11.57 8.482E-01 87.55 -61.1082 -4.3076 -4.3076 0.0014 -89.99 LEFT

90.00 255.00 1.233E-03 -10.79 8.065E-01 89.19 -61.0561 -4.7456 -4.7456 0.0015 -89.98 LEFT

90.00 256.00 1.241E-03 -10.08 7.631E-01 90.85 -61.0048 -5.2252 -5.2252 0.0016 -89.98 LEFT

90.00 257.00 1.248E-03 -9.42 7.182E-01 92.52 -60.9550 -5.7520 -5.7520 0.0017 -89.98 LEFT

90.00 258.00 1.255E-03 -8.81 6.718E-01 94.19 -60.9071 -6.3328 -6.3328 0.0018 -89.98 LEFT

90.00 259.00 1.261E-03 -8.26 6.238E-01 95.87 -60.8615 -6.9762 -6.9762 0.0020 -89.97 LEFT

90.00 260.00 1.267E-03 -7.76 5.744E-01 97.56 -60.8186 -7.6937 -7.6937 0.0021 -89.97 LEFT

90.00 261.00 1.273E-03 -7.31 5.234E-01 99.25 -60.7789 -8.5001 -8.5001 0.0023 -89.96 LEFT

90.00 262.00 1.279E-03 -6.92 4.711E-01 100.94 -60.7426 -9.4159 -9.4159 0.0026 -89.95 LEFT

90.00 263.00 1.283E-03 -6.57 4.172E-01 102.64 -60.7099 -10.4697 -10.4697 0.0029 -89.94 LEFT

90.00 264.00 1.288E-03 -6.27 3.620E-01 104.34 -60.6812 -11.7037 -11.7036 0.0033 -89.93 LEFT

90.00 265.00 1.291E-03 -6.02 3.053E-01 106.05 -60.6565 -13.1832 -13.1831 0.0039 -89.91 LEFT

90.00 266.00 1.294E-03 -5.81 2.472E-01 107.75 -60.6362 -15.0180 -15.0179 0.0048 -89.88 LEFT

90.00 267.00 1.297E-03 -5.65 1.876E-01 109.45 -60.6202 -17.4139 -17.4137 0.0063 -89.83 LEFT

90.00 268.00 1.298E-03 -5.54 1.265E-01 111.15 -60.6087 -20.8332 -20.8328 0.0092 -89.74 LEFT

90.00 269.00 1.299E-03 -5.47 6.402E-02 112.84 -60.6018 -26.7516 -26.7498 0.0179 -89.45 LEFT

90.00 270.00 1.300E-03 -5.45 0.000E+00 0.00 -60.5995 -999.9999 -60.5995 0.0000 0.00 LINEAR

90.00 271.00 1.299E-03 -5.47 6.554E-02 -63.79 -60.6018 -26.5476 -26.5459 0.0169 89.40 RIGHT

90.00 272.00 1.298E-03 -5.54 1.326E-01 -62.11 -60.6087 -20.4251 -20.4246 0.0082 89.69 RIGHT

90.00 273.00 1.297E-03 -5.65 2.013E-01 -60.44 -60.6202 -16.8012 -16.8010 0.0053 89.79 RIGHT

90.00 274.00 1.294E-03 -5.81 2.716E-01 -58.78 -60.6362 -14.2002 -14.2001 0.0038 89.84 RIGHT

90.00 275.00 1.291E-03 -6.02 3.435E-01 -57.14 -60.6565 -12.1596 -12.1595 0.0029 89.86 RIGHT

90.00 276.00 1.288E-03 -6.27 4.171E-01 -55.50 -60.6812 -10.4733 -10.4733 0.0023 89.88 RIGHT

90.00 277.00 1.283E-03 -6.57 4.924E-01 -53.88 -60.7099 -9.0316 -9.0315 0.0019 89.90 RIGHT

90.00 278.00 1.279E-03 -6.92 5.694E-01 -52.27 -60.7426 -7.7686 -7.7686 0.0016 89.91 RIGHT

90.00 279.00 1.273E-03 -7.31 6.483E-01 -50.68 -60.7789 -6.6423 -6.6422 0.0013 89.92 RIGHT

90.00 280.00 1.267E-03 -7.76 7.289E-01 -49.10 -60.8186 -5.6236 -5.6236 0.0011 89.93 RIGHT

90.00 281.00 1.261E-03 -8.26 8.115E-01 -47.55 -60.8615 -4.6920 -4.6920 0.0010 89.93 RIGHT

90.00 282.00 1.255E-03 -8.81 8.959E-01 -46.00 -60.9071 -3.8323 -3.8323 0.0008 89.94 RIGHT

90.00 283.00 1.248E-03 -9.42 9.822E-01 -44.48 -60.9550 -3.0330 -3.0330 0.0007 89.94 RIGHT

90.00 284.00 1.241E-03 -10.08 1.071E+00 -42.98 -61.0048 -2.2852 -2.2852 0.0006 89.94 RIGHT

90.00 285.00 1.233E-03 -10.79 1.161E+00 -41.50 -61.0561 -1.5818 -1.5818 0.0005 89.95 RIGHT



__________________________________________________________________________________ PAGE 118

90.00 286.00 1.226E-03 -11.57 1.253E+00 -40.04 -61.1082 -0.9172 -0.9172 0.0005 89.95 RIGHT

90.00 287.00 1.219E-03 -12.40 1.348E+00 -38.61 -61.1606 -0.2867 -0.2867 0.0004 89.95 RIGHT

90.00 288.00 1.211E-03 -13.28 1.444E+00 -37.19 -61.2126 0.3136 0.3136 0.0003 89.96 RIGHT

90.00 289.00 1.204E-03 -14.22 1.542E+00 -35.80 -61.2636 0.8867 0.8867 0.0003 89.96 RIGHT

90.00 290.00 1.197E-03 -15.22 1.643E+00 -34.43 -61.3127 1.4353 1.4353 0.0002 89.96 RIGHT

90.00 291.00 1.191E-03 -16.28 1.746E+00 -33.09 -61.3593 1.9618 1.9618 0.0002 89.96 RIGHT

90.00 292.00 1.185E-03 -17.39 1.850E+00 -31.78 -61.4025 2.4681 2.4681 0.0002 89.96 RIGHT

90.00 293.00 1.180E-03 -18.55 1.957E+00 -30.48 -61.4415 2.9557 2.9557 0.0001 89.97 RIGHT

90.00 294.00 1.175E-03 -19.76 2.066E+00 -29.22 -61.4755 3.4262 3.4262 0.0001 89.97 RIGHT

90.00 295.00 1.171E-03 -21.02 2.177E+00 -27.98 -61.5036 3.8808 3.8808 0.0001 89.97 RIGHT

90.00 296.00 1.168E-03 -22.32 2.290E+00 -26.77 -61.5252 4.3206 4.3206 0.0000 89.97 RIGHT

90.00 297.00 1.167E-03 -23.66 2.405E+00 -25.58 -61.5393 4.7465 4.7465 0.0000 89.97 RIGHT

90.00 298.00 1.166E-03 -25.03 2.523E+00 -24.42 -61.5454 5.1594 5.1594 0.0000 89.97 LINEAR

90.00 299.00 1.166E-03 -26.42 2.642E+00 -23.28 -61.5428 5.5601 5.5601 0.0000 89.97 LEFT

90.00 300.00 1.168E-03 -27.84 2.763E+00 -22.18 -61.5310 5.9491 5.9491 0.0000 89.98 LEFT

90.00 301.00 1.171E-03 -29.26 2.885E+00 -21.10 -61.5097 6.3271 6.3271 0.0001 89.98 LEFT

90.00 302.00 1.175E-03 -30.69 3.010E+00 -20.04 -61.4786 6.6946 6.6946 0.0001 89.98 LEFT

90.00 303.00 1.180E-03 -32.11 3.137E+00 -19.02 -61.4377 7.0520 7.0520 0.0001 89.98 LEFT

90.00 304.00 1.187E-03 -33.52 3.265E+00 -18.02 -61.3869 7.3998 7.3998 0.0001 89.98 LEFT

90.00 305.00 1.195E-03 -34.90 3.395E+00 -17.05 -61.3266 7.7383 7.7383 0.0001 89.98 LEFT

90.00 306.00 1.205E-03 -36.26 3.526E+00 -16.10 -61.2570 8.0680 8.0680 0.0001 89.98 LEFT

90.00 307.00 1.216E-03 -37.58 3.659E+00 -15.18 -61.1787 8.3890 8.3890 0.0001 89.98 LEFT

90.00 308.00 1.228E-03 -38.85 3.793E+00 -14.29 -61.0922 8.7016 8.7016 0.0001 89.98 LEFT

90.00 309.00 1.241E-03 -40.08 3.928E+00 -13.42 -60.9985 9.0062 9.0062 0.0001 89.98 LEFT

90.00 310.00 1.256E-03 -41.24 4.065E+00 -12.58 -60.8982 9.3030 9.3030 0.0001 89.98 LEFT

90.00 311.00 1.271E-03 -42.35 4.202E+00 -11.77 -60.7923 9.5920 9.5920 0.0002 89.99 LEFT

90.00 312.00 1.288E-03 -43.38 4.341E+00 -10.98 -60.6817 9.8736 9.8736 0.0002 89.99 LEFT

90.00 313.00 1.305E-03 -44.35 4.480E+00 -10.21 -60.5676 10.1480 10.1480 0.0002 89.99 LEFT

90.00 314.00 1.322E-03 -45.25 4.620E+00 -9.47 -60.4508 10.4151 10.4151 0.0002 89.99 LEFT

90.00 315.00 1.340E-03 -46.07 4.760E+00 -8.76 -60.3323 10.6753 10.6753 0.0002 89.99 LEFT

90.00 316.00 1.359E-03 -46.81 4.901E+00 -8.06 -60.2133 10.9286 10.9286 0.0002 89.99 LEFT

90.00 317.00 1.378E-03 -47.48 5.042E+00 -7.40 -60.0947 11.1752 11.1752 0.0002 89.99 LEFT

90.00 318.00 1.396E-03 -48.07 5.183E+00 -6.75 -59.9773 11.4152 11.4152 0.0002 89.99 LEFT

90.00 319.00 1.415E-03 -48.58 5.325E+00 -6.13 -59.8623 11.6486 11.6486 0.0002 89.99 LEFT

90.00 320.00 1.433E-03 -49.01 5.466E+00 -5.53 -59.7503 11.8756 11.8756 0.0002 89.99 LEFT

90.00 321.00 1.451E-03 -49.37 5.606E+00 -4.96 -59.6422 12.0962 12.0962 0.0002 89.99 LEFT

90.00 322.00 1.469E-03 -49.65 5.746E+00 -4.40 -59.5389 12.3106 12.3106 0.0002 89.99 LEFT

90.00 323.00 1.485E-03 -49.85 5.886E+00 -3.87 -59.4410 12.5188 12.5188 0.0002 89.99 LEFT

90.00 324.00 1.501E-03 -49.98 6.024E+00 -3.36 -59.3492 12.7209 12.7209 0.0002 89.99 LEFT

90.00 325.00 1.516E-03 -50.04 6.162E+00 -2.87 -59.2641 12.9169 12.9169 0.0002 89.99 LEFT

90.00 326.00 1.529E-03 -50.03 6.298E+00 -2.40 -59.1865 13.1069 13.1069 0.0002 89.99 LEFT

90.00 327.00 1.542E-03 -49.94 6.433E+00 -1.95 -59.1167 13.2910 13.2910 0.0002 89.99 LEFT

90.00 328.00 1.553E-03 -49.79 6.566E+00 -1.51 -59.0554 13.4692 13.4692 0.0002 89.99 LEFT

90.00 329.00 1.562E-03 -49.57 6.698E+00 -1.10 -59.0031 13.6416 13.6416 0.0002 89.99 LEFT

90.00 330.00 1.570E-03 -49.28 6.828E+00 -0.71 -58.9601 13.8082 13.8082 0.0002 89.99 LEFT

90.00 331.00 1.576E-03 -48.93 6.955E+00 -0.33 -58.9271 13.9690 13.9690 0.0002 89.99 LEFT

90.00 332.00 1.580E-03 -48.51 7.081E+00 0.03 -58.9043 14.1241 14.1241 0.0002 89.99 LEFT

90.00 333.00 1.582E-03 -48.02 7.203E+00 0.37 -58.8923 14.2735 14.2735 0.0002 89.99 LEFT

90.00 334.00 1.582E-03 -47.47 7.324E+00 0.70 -58.8914 14.4173 14.4173 0.0002 89.99 LEFT

90.00 335.00 1.580E-03 -46.86 7.441E+00 1.01 -58.9020 14.5555 14.5555 0.0002 89.99 LEFT

90.00 336.00 1.576E-03 -46.18 7.556E+00 1.30 -58.9244 14.6880 14.6880 0.0002 89.99 LEFT

90.00 337.00 1.570E-03 -45.44 7.667E+00 1.58 -58.9591 14.8150 14.8150 0.0001 89.99 LEFT

90.00 338.00 1.562E-03 -44.63 7.775E+00 1.84 -59.0064 14.9365 14.9365 0.0001 89.99 LEFT

90.00 339.00 1.551E-03 -43.75 7.879E+00 2.09 -59.0666 15.0524 15.0524 0.0001 89.99 LEFT

90.00 340.00 1.538E-03 -42.81 7.980E+00 2.33 -59.1401 15.1629 15.1629 0.0001 89.99 LEFT

90.00 341.00 1.522E-03 -41.80 8.077E+00 2.55 -59.2273 15.2678 15.2678 0.0001 89.99 LEFT

90.00 342.00 1.505E-03 -40.71 8.170E+00 2.76 -59.3285 15.3673 15.3673 0.0001 89.99 LEFT

90.00 343.00 1.485E-03 -39.55 8.259E+00 2.95 -59.4440 15.4614 15.4614 0.0001 89.99 LEFT

90.00 344.00 1.463E-03 -38.31 8.344E+00 3.14 -59.5741 15.5500 15.5500 0.0001 89.99 LEFT

90.00 345.00 1.438E-03 -36.98 8.424E+00 3.31 -59.7193 15.6332 15.6332 0.0001 89.99 LEFT

90.00 346.00 1.412E-03 -35.57 8.500E+00 3.46 -59.8797 15.7110 15.7110 0.0001 89.99 LEFT

90.00 347.00 1.384E-03 -34.07 8.571E+00 3.61 -60.0558 15.7834 15.7834 0.0001 89.99 LEFT

90.00 348.00 1.354E-03 -32.47 8.637E+00 3.75 -60.2477 15.8504 15.8504 0.0001 89.99 LEFT

90.00 349.00 1.322E-03 -30.77 8.699E+00 3.87 -60.4557 15.9120 15.9120 0.0001 89.99 LEFT

90.00 350.00 1.288E-03 -28.95 8.755E+00 3.99 -60.6799 15.9682 15.9682 0.0001 89.99 LEFT

90.00 351.00 1.253E-03 -27.01 8.807E+00 4.09 -60.9204 16.0191 16.0191 0.0001 89.99 LEFT

90.00 352.00 1.216E-03 -24.94 8.853E+00 4.18 -61.1772 16.0646 16.0646 0.0001 89.99 LEFT

90.00 353.00 1.179E-03 -22.72 8.894E+00 4.27 -61.4501 16.1048 16.1048 0.0001 89.99 LEFT

90.00 354.00 1.140E-03 -20.35 8.930E+00 4.34 -61.7388 16.1396 16.1396 0.0001 89.99 LEFT

90.00 355.00 1.101E-03 -17.80 8.960E+00 4.41 -62.0427 16.1690 16.1690 0.0000 89.99 LEFT

90.00 356.00 1.061E-03 -15.06 8.985E+00 4.46 -62.3607 16.1932 16.1932 0.0000 89.99 LEFT

90.00 357.00 1.022E-03 -12.11 9.005E+00 4.50 -62.6915 16.2119 16.2119 0.0000 89.99 LEFT

90.00 358.00 9.822E-04 -8.93 9.018E+00 4.54 -63.0331 16.2254 16.2254 0.0000 89.99 LEFT

90.00 359.00 9.434E-04 -5.50 9.027E+00 4.56 -63.3829 16.2335 16.2335 0.0000 89.99 LEFT

90.00 360.00 9.057E-04 -1.80 9.030E+00 4.58 -63.7374 16.2362 16.2362 0.0000 89.99 LEFT



__________________________________________________________________________________ PAGE 119

Horizontal HPBW is 66.66o

Main beam gain 16.24dB

Gain drop for 120o beam to 5.95dB

Front-to-back radio (FtB) for 180o drops to the level of 17dB

FtB truncation (without 90o and 270o as linear to antenna axis) calculated as suppression for 120o

beam (estimated for 90-180o) is 21.2 dB.

Table 24 Values of the scattered electric field strength in the far field in V

LOCATION ETHETA EPHI directivity in dB POLARISATION

THETA PHI magn. phase magn. phase vert. horiz. total axial r. angle direction

0.00 0.00 0.000E+00 0.00 3.450E-01 -101.28 -999.9999 -12.1198 -12.1198 0.0000 90.00 LINEAR

1.00 0.00 1.267E-04 -43.21 3.453E-01 -100.68 -80.8205 -12.1144 -12.1144 0.0003 89.99 RIGHT

2.00 0.00 2.536E-04 -43.22 3.452E-01 -100.27 -74.7950 -12.1161 -12.1161 0.0006 89.98 RIGHT

3.00 0.00 3.807E-04 -43.25 3.448E-01 -100.07 -71.2653 -12.1264 -12.1263 0.0009 89.97 RIGHT

4.00 0.00 5.082E-04 -43.28 3.440E-01 -100.10 -68.7558 -12.1470 -12.1470 0.0012 89.95 RIGHT

5.00 0.00 6.363E-04 -43.32 3.427E-01 -100.37 -66.8044 -12.1800 -12.1800 0.0016 89.94 RIGHT

6.00 0.00 7.649E-04 -43.37 3.408E-01 -100.92 -65.2057 -12.2269 -12.2269 0.0019 89.93 RIGHT

7.00 0.00 8.940E-04 -43.43 3.384E-01 -101.77 -63.8504 -12.2892 -12.2892 0.0022 89.92 RIGHT

8.00 0.00 1.024E-03 -43.49 3.353E-01 -102.98 -62.6735 -12.3678 -12.3678 0.0026 89.91 RIGHT

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337.00 0.00 2.770E-03 135.53 2.519E-01 -147.31 -54.0278 -14.8543 -14.8538 0.0107 -90.14 LEFT

338.00 0.00 2.694E-03 135.56 2.648E-01 -144.77 -54.2697 -14.4190 -14.4185 0.0100 -90.10 LEFT

339.00 0.00 2.607E-03 135.60 2.763E-01 -142.20 -54.5555 -14.0506 -14.0502 0.0093 -90.07 LEFT

340.00 0.00 2.510E-03 135.65 2.864E-01 -139.61 -54.8840 -13.7392 -13.7389 0.0087 -90.05 LEFT

341.00 0.00 2.405E-03 135.71 2.952E-01 -137.02 -55.2544 -13.4762 -13.4760 0.0081 -90.02 LEFT

342.00 0.00 2.294E-03 135.77 3.028E-01 -134.44 -55.6666 -13.2547 -13.2545 0.0076 90.00 LEFT

343.00 0.00 2.177E-03 135.83 3.093E-01 -131.88 -56.1210 -13.0686 -13.0683 0.0070 90.02 LEFT

344.00 0.00 2.056E-03 135.90 3.149E-01 -129.36 -56.6186 -12.9126 -12.9124 0.0065 90.03 LEFT

345.00 0.00 1.931E-03 135.98 3.197E-01 -126.89 -57.1614 -12.7821 -12.7820 0.0060 90.04 LEFT

346.00 0.00 1.804E-03 136.06 3.237E-01 -124.48 -57.7523 -12.6733 -12.6732 0.0055 90.05 LEFT

347.00 0.00 1.675E-03 136.13 3.271E-01 -122.14 -58.3952 -12.5825 -12.5824 0.0050 90.06 LEFT

348.00 0.00 1.546E-03 136.21 3.300E-01 -119.87 -59.0958 -12.5068 -12.5067 0.0045 90.06 LEFT

349.00 0.00 1.415E-03 136.29 3.324E-01 -117.68 -59.8616 -12.4433 -12.4432 0.0041 90.07 LEFT

350.00 0.00 1.284E-03 136.37 3.345E-01 -115.58 -60.7029 -12.3897 -12.3896 0.0037 90.07 LEFT

351.00 0.00 1.154E-03 136.44 3.363E-01 -113.59 -61.6337 -12.3440 -12.3439 0.0032 90.07 LEFT

352.00 0.00 1.024E-03 136.51 3.378E-01 -111.70 -62.6735 -12.3046 -12.3045 0.0028 90.06 LEFT

353.00 0.00 8.940E-04 136.57 3.391E-01 -109.92 -63.8504 -12.2700 -12.2700 0.0024 90.06 LEFT

354.00 0.00 7.649E-04 136.63 3.403E-01 -108.26 -65.2057 -12.2394 -12.2394 0.0020 90.05 LEFT

355.00 0.00 6.363E-04 136.68 3.414E-01 -106.74 -66.8044 -12.2119 -12.2119 0.0017 90.05 LEFT

356.00 0.00 5.082E-04 136.72 3.424E-01 -105.34 -68.7558 -12.1872 -12.1872 0.0013 90.04 LEFT

357.00 0.00 3.807E-04 136.75 3.432E-01 -104.09 -71.2653 -12.1652 -12.1652 0.0010 90.03 LEFT

358.00 0.00 2.536E-04 136.78 3.440E-01 -102.99 -74.7950 -12.1462 -12.1462 0.0006 90.02 LEFT

359.00 0.00 1.267E-04 136.79 3.446E-01 -102.05 -80.8205 -12.1308 -12.1308 0.0003 90.01 LEFT

360.00 0.00 0.000E+00 0.00 3.450E-01 -101.28 -999.9999 -12.1198 -12.1198 0.0000 90.00 LINEAR



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Vertical HPBW is 11.83o

First minimum for -13o suppression 24.85 dB

Upper side lobe for +19o suppression 12.95 dB

The directivity gain is based on an active power of 3.23502E-02W and on a power loss of 0.00000E+00 W

Table 25 Simulation times (seconds)

CPU-time runtime

Reading and constructing the geometry 0.015 0.015

Checking the geometry 0.016 0.016

Initialisation of the Greens function 0.000 0.000

Calcul. of coupling for PO/Fock 0.000 0.000

Calcul. of matrix elements 5.694 5.694

Calcul. of right-hand side vector 0.000 0.000

Preconditioning system of linear eqns. 0.047 0.047

Solution of the system of linear eqns. 0.686 0.686

Determination of surface currents 0.000 0.000

Calcul. of impedances/powers/losses 0.000 0.000

Calcul. of averaged SAR values 0.000 0.000

Calcul. of power ideal receiving ant. 0.000 0.000

Calcul. of cable coupling 0.000 0.000

Calcul. of electric near field 0.000 0.000

Calcul. of magnetic near field 0.000 0.000

Calcul. of far field 0.702 0.702

Total times: 7.160 7.160

Peak memory usage during the whole solution: 12.208 MByte

Finished: 2013-04-04 14:18:22



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Appendix C: Simulation conditions for 6-sector capacity analysis

Assumptions A hexagonal cellular layout composed of 19 sites is assumed in the simulation study for 6-sector sites capacity gain estimation- as presented on

Figure 89 Simulation configuration for 3- and 6-sector site

The location of users is randomly generated from a uniform distribution within the center area

(center site and first ring). The serving sector is selected among all sectors of the center area with the

highest received signal power, that is calculated including pathloss and shadow fading but excluding

fast fading. A total of 60 users per site is considered and scaled per sector according to the number of

sectors, resulting in 20 users/sector for 3-sector site and 10 users/sector for 6-sector site. The infinite

full buffer traffic model has been chosen for the simulations, therefore all BSs have always data to

transmit to every attached UEs. In addition, the Proportional Fair (PF) scheduler1 has been selected

as frequency domain packet scheduler [25]. The minimum loss in signals between BS and UE and it is

defined as Minimum Coupling Loss (MCL) - the minimum distance loss including antenna gains

measured between antenna connectors [26]. In a macro cell deployment, MCL is set equal to 70 dB

for urban area and 80 dB for rural area. With the above definition, the received power in downlink

and uplink can be expressed as:

` (40)

Where PTX –power transmitted and GTX transmit antenna gain and GRX receive antenna gain, the pathloss L(r) is expressed as:

(41)

where hBTS is the base station antenna height measured from the average rooftop level in [m], r is the

UE-BS distance in [Km], and f is the carrier frequency in [MHz]. In this simulations hBTS is set to 15 m

and f to 2600 MHz.

The shadow fading is modeled by the Claussen model presented in [27].It generates for every site a

lognormal-distributed 2D space-correlated shadow fading map. The parameters of the model are

reported in Table 26.



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Table 26 Parameters of the Claussen model for the shadow fading

Parameter Value

Map resolution 5 m/pixel

Number of neighbors 8

Mean 0

Standard deviation 8 dB

Inter-site correlation 0.5

Intra-site correlation 1

The number of neighbors indicates the number of pixels the algorithm takes into account when the

space-correlated maps are generated. Inter-site correlation is the shadow fading correlation between

maps of different sites. Similarly, intrasite correlation is the shadow fading correlation between maps

of different sectors of the same site. In this case, it is set to 1 indicating that sectors of the same site

will have the same shadow fading map.

The fast fading is generated using the Rosa Zheng model [28]. The considered channel models

includes the Extended Pedestrian B, for users' speed of 3 km/h, and the Extended Vehicular A, for

users' speed of 30 km/h. These models are presented in [29] as extensions of the ITU Pedestrian B

and ITU Vehicular A for channels with bandwidth larger than 5 MHz. Table 27 summarizes the

simulation parameters used.

Table 27 Main parameters and simulation assumptions

PARAMETER VALUE

Carrier Frequency 2.6 GHz

System Bandwidth 10 MHz

No. of Subcarriers 600

No. of PRBs 50 (12 Subcarriers/PRB)

Subframe Duration 1 ms (14 OFDM Symbols)

Total BS Transmit Power 46 dBm (1-Tx Antenna)

Transmission Scheme 2x2 OLSM

HARQ Model Not implemented

Uplink delay 2 TTIs

No. of Sectors per Site 3 or 6

No. of UEs 20 UEs/sector (for 3-sector site) or 10 UEs/sector (for 6-sector site)

Power Delay Profile Extended Pedestrian-B, Extended Vehicule-A

Users' speed 3 km/h, 30 km/h

BLER Target 10%

Cellular Layout Hexagonal grid with 19 sites

Inter-site Distance 500 m

Minimum Coupling Loss 70 dB

Interfering cells First interfering ring

Simulation Time 100 TTIs



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For presented simulation results a real radiation patterns has been selected. For the 3-sectorsite

deployment, the horizontal radiation pattern of the antenna Kathrein 80010622 has been considered

for a frequency of 2620 MHz, -45o polarization, and 5o downtilt. For the 6-sectorsite deployment, no

radiation pattern with HPBW of 33o were available for a frequency of 2600 MHz. Therefore, we

adopted the horizontal radiation pattern of the antenna Kathrein 80010251 that has been measured

at 2140 MHz, -45o polarization, and 5o downtilt. Selected antenna pattern are presented on Figure

90.

Figure 90 Antenna patterns used for simulations

Metrics - Site Capacity and Capacity Gain

This paragraph introduces the definitions of site capacity and capacity gain that are used in

subsection 3.5.6. We assume that user applications require a throughput of at least 300 Kbps. Below

this value, the user's expectations for the application are not satisfied. In order to guarantee a certain

level of QoS for the users, service providers are required to offer a throughput higher than 300 Kbps

for at least 90% of the users. In other words, the percentage of users with throughput lower than 300

Kbps should be kept below 10%. According to this requirement, site capacity is defined as the

average site throughput and the average number of UEs in the site, when the percentage of UEs with

throughput lower than 300 Kbps is 10%. Capacity gain is defined as the ratio of the 6-sector-site

capacity and the 3-sectorsite capacity. These definitions allow for a fair comparison of the

performance of the two deployments because both are evaluated at the same load conditions. The

other metrics are provided in 155. Capacity evaluation for alternative scenarios

Four scenarios are considered with different users' speeds, CQI compression techniques, and

feedback delays. The parameters are summarized in Table 28

Table 28 Capacity evaluations scenarios

Scenario Users' speed CQI compression Uplink scheme delay

1 3 km/h uncompressed 2 TTI



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3 3 km/h wideband 2 TTI


In the uncompressed scheme, the CQI feedback consists of one CQI value for each PRB, while in the

wideband scheme, the CQI feedback consists of one single value calculated as the average CQI

among the PRBs. The feedback delay corresponds to the delay between the time the user measures

and generates the feedback information and the time the base station uses these information for

scheduling and link adaptation. Each scenario has been simulated with different numbers of users

per site equally distributed among the sectors. The results are presented on Figure 91 and on Figure

92 respectively.

Figure 91 Capacity simulations results for 4 scenarios for 3 sector site



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Figure 92 Capacity simulations results for 4 scenarios for 6 sector site

Evaluation cases for both UE numbers and throughput per site indicate the capacity gain on the level

of +59% up to +89% as presented on Table 29 Summary of site capacities and capacity gains.

Table 29 Summary of site capacities and capacity gains for 3-/ 6-sector sites

Scenario ID 3-sector site capacity 6-sector site capacity Capacity Gain

1 44 UEs 72 UEs 1.64

1 37.56 Mbps 64.86 Mbps 1.73

2 20 UEs 36 UEs 1.80

2 18.22 Mbps 34.45 Mbps 1.89

3 24 UEs 39 UEs 1.63

3 24.80 Mbps 44.10 Mbps 1.78

4 39 UEs 62 UEs 1.59

4 33.19 Mbps 58.10 Mbps 1.75



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Appendix D: Measurement conditions of antenna array for 6-sector

The instruments that have been used in the measurements are:

• 1x Aaronia Hyperlog 7060 (Tx antenna)

• 1x Kathrein 80010622 (Rx antenna)

• 1x SiteMaster S251B

• 1x Power splitter/combiner

• Tripods, coaxial-cables, connectors, adapters

The parameters and settings of the measurements are summarized below:

• Frequency of the transmitted signal: 2500 MHz (maximum allowed by the signal generator in the

SiteMaster S251B)

• Distance Tx-Rx: 30 meters (far-field region). It has been chosen as 2D2=λ with D being the largest

dimension of the antenna aperture

• Angular rotation of the Rx antenna: steps of 3o between -90o and +90o

On Figure 93 is presented configuration for reference and 6-sector antenna array measurements.

Figure 93 Measurement configuration for reference case and antenna array



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Appendix E: Measurement conditions for optimal downtilts in urban environment

The field measurements were done under European Commission’s seventh framework program FP7-

ICT-2009 under grant agreement n° 247223. The testbed used for investigations consists of stations

BS1 and BS2 at the two different sites "Lennéplatz", and “HBF”. The height of the base stations BS1

and BS2 is around 50 m; average building height of other residential buildings in the surroundings is

between 15 and 20 m. The downtilt of the BS antennas can be adjusted electronically from 6° to 15°

with step of 1°. On street level, a test UE has been mounted on a rickshaw that moves along drive

routes and measures the receive power level at 38 measurement points. The test UE was equipped

with two dipole antennas placed about 40 cm apart on a rotation table. The measurement hardware

enabled the estimation of the channel transfer function (CTF) via reference symbols (RS) that are

transmitted twice every 1 ms (in every slot) for each antenna on every sixth orthogonal carriers over

a bandwidth of 20MHz. To guarantee sufficient averaging of small scale fading, data from five

different antenna positions was collected at every location using the rotation table. Each

measurement was taken for a duration of 30 ms. The measurements were done in the downlink.

Figure 94 Dresden testbed environment

The umbrella coverage provided by 2 testbed sites (locations presented on Figure 94) indicate that

for location close to the site significantly high downtilts need to be concerned to improve the signal–

to–interference-ratio (SIR).



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Appendix F: VS simulations conditions & details of outputs

PRELIMINARY STATIC SIMULATIONS

Antenna pattern based on 3GPP model does not provide realistic vertical sectorisation results. The

antenna patterns that indicate sidelobes and zeros on the characteristic have been used for

simulations.

Figure 95 3x1 total tilt=12: 7° mechanical, 5°electrical

On Figure 95 antenna pattern for reference case is presented. The total downtilt 12o is used the

HPBW for vertical plane is 6.8o. On Figure 96 antenna pattern for outer cell is presented. The total

downtilt 10o is used and is very similar to reference case; that outer cell in vertical sectorisation

concept will be overlapped by introducing inner cell with different cell ID.

Figure 96 3x2 Outer total tilt=10°: 7° mechanical, 3°electrical



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Finally on Figure 97 inner cell radiation path is presented. Higher sidelobes were assumed however

both highest below -12dB. Total downtilt for inner cell is 18o. HPBW for vertical plane is 4o.

Figure 97 3x2 Inner total tilt=18°: 7° mechanical, 11°electrical

Mechanical downtilts are reduced to 7o in order to keep desired coverage and avoid distortion as

presented on Figure 81, page 98.

Typical propagation model has been used as described in Table 27, page 126. Additionally Table 30

represents specific parameters for vertical sectorisation simulations.

Table 30 Simulation vertical parameter settings

Reference Vertical Sectorization

Sectors 3x1 3x2

Power 46dBm 43dBm+43dBm

Half Power Beam Width [°] 6.8 4

Tilt[°] 12 10(outer), 18(inner)

RESULT 1:

Analysis of SINR have been done for reference configuration and 3x2. As presented on CDF function

for individual inner and outer cells the result are close to reference however due to increased

interference caused by overlapping inner and outer cell overall SINR for 3x2 is 0.5 up to 5dB lower

than for reference.



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Figure 98 SINR for vertical sectorisation: innercell, outercell and combined 3x2 case

RESULT 2:

Figure 99 UE throughput for outer cell: separated on losses <1 and gains >1

As throughput is concerned outer cell is mainly suffering due to vertical sectorisation and area of

outer cell affected by throughput degradation is c.a. 80% of entire outer cell. On the cell border with

inner cell a high interference causes significant losses – throughput drops to 20% of reference case.

Detail results are shown on Figure 99.



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Figure 100 UE throughput for inner cell: separated on losses <1 and gains >1

Inner cell users obtain a significant improvement of throughput. Area affected by throughput loss in

inner is below c.a. 5%. Majority of UE experience throughput gain which can be as high as 10x

increase (10% of coverage of inner cell). Details presented on Figure 100.

RESULT 3:

Figure 101 Inner and outer cell size

Inner cell takes 18% of reference 3x1 cell size, outer cell takes 82% of reference 3x1 cell size. Results




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RESULT 4:

Signal level decreases due to noise floor increase by overlapping both beams

Figure 102 RSSI for reference 3x1 case

Figure 103 RSSI for vertical sectorisation 3x2 case: outer and innercell

As can be observed on by comparison reference case received signal level (Figure 102) and case 3x2

(Figure 103) a degradation of signal strength is observed in outer cell. Also impact of low sidelobes of

outer beam is visible however impact on inner cell is low. This phenomena indicates why potential

degradation of outer cell users should be expected.



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RESULT 5:

Handoff area increase. Number of handoffs increase from 17% (3x1) to 27% (3x2).

Figure 104 Handoff area for reference case 3x1

Figure 105 Handoff area for reference case outer and inner cell3x2

For vertical sectorisation due to multiplying number of Cell_ID additional area of handovers (HO)is

introduced. The main area affected by increase HO is inner cell as lower sidelobes of outer cell and

zeros on inner cell characteristic causes situation of local high interference with lack of dominant

serving cell. Results are presented on Figure 104, Figure 105. This phenomena is also observed in

dynamic traffic simulations based on real digital map layers.



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RESULT 6:

SINR level decreases for vertical sectorisation which indicates that overall network efficiency

degraded. The phenomena are presented on Figure 106 to Figure 108.

Figure 106 Reference (3x1) SINR level Figure 107 Difference of SINR 3x1 vs 3x2

Figure 108 SINR level for 3x2 case inner cell and SINR level for 3x2 case outer cell

RESULT 7:

A file size of 1Mbits has been used for simulation the load. Mean time of time transmission in

relation to Intensity (with increasing λ, as file size stays the same; E(σ)=106) has been examined. On

Figure 109 results are presented. In majority of range transmission time for standard 3x1

configuration is shorter than 3x2.



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Figure 109 Time transfer for 3x1 and 3x2 configuration with increasing λ and E(σ)=106

In majority of intensity range transmission time for standard 3x1 configuration is shorter than 3x2.

Only for high intensity, close to congestion situation, advantage of 3x2 is observed. However

transmission time for both cases rapidly increases significantly. Effect observed by end user of

exponential growth of load-time cannot be compensated by obtaining slightly higher intensity. The

potential overall gain could be difficult to obtain as intensity range is out of optimal range of site

load.

RESULT 8:

Gain in vertical sectorisation is traffic depended. As majority of throughput gain is generated in inner

cell which has limited coverage (18% of reference 3x1 configuration) a high load need to appear.

With equal distribution of traffic among simulated area UE low number of UE causes degradation of

capacity. Detail results are presented on Figure 110.

Figure 110 Gain throughput distribution for vertical sectorisation vs load

The presented results are strongly related to traffic model and can vary in case of traffic model

change, however presented drawbacks is further investigated in dynamic simulations.



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DYNAMIC SIMULATOR

As a next step of analysis a dynamic simulator has been used for evaluation results 1-8. Two layers of

simulations have been available. The first one a “snapshot” - traditional way of randomly distributed

users in serving area with steady states and mean values generated over number of simulations –


Figure 111 UE’s distribution in static snapshot simulation

A dynamic simulator16 with moving users according mobility model and mean values taken on full

time simulation has been used. Simulated users locations are presented on Figure 112 (where “S” is

simulation counter) Simulator randomly generates user activity with different mobility paths

according to used model (Pedestrian A 3km/h). A single user motion for S=600 is presented on Figure

113.

The results allow deeper analysis of vertical sectorisation and evaluate the dependency of the

feature form traffic modeling. As preliminary static simulations indicate gain in range 24% - 55%

depending on traffic model, advanced simulations on dynamic traffic model could deliver more

precise answers.

16 MoRSE is a dynamic system level simulator which reflects real user behavior and is aligned with NSN’s product and

algorithms



__________________________________________________________________________________ PAGE 144

Figure 112 Simulated UE’s with mobility patterns

Figure 113 Sample of user motion used by dynamic simulator



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Figure 114 Antenna patterns (vertical and horizontal) for dynamic simulations

For the dynamic simulator presented on Figure 114 antenna pattern has been used. Antenna pattern provided to simulator inputs has been based on anechoic chamber measurement of prototype, however as visible some inaccuracy regarding front-to-back ration can be observed. In Table 31 set of simulation configuration parameters are presented. Table 31 Dynamic simulations parameters

Configurations parameters Value

BS Antenna Gain 16.6 – 18dBi (tilt -10deg/0deg)

Downtilt for 3x1 case -5deg (mechanical)

Downtilt for 3x2 case Inner:-10deg (-5deg) Outer:0deg (-5deg)

BS Antenna Height 30m

UE Antenna Omnidirectional

ISD average 840m

Network topology 31 sectors

Channel Model Pedestrian A 3km/h

Shadowing 7dB

Operational band 2100MHz

BandWidth 10MHz

NoisePowerDownlink ‐114.4473dBm

NoisePowerUplink ‐119.4473dBm

SlowFadingType Autoregressive

sigma 8dB

DL_CQIMeasurementMode Mode‐2

HOAlgorithm PowerBudget

HO_Margin 2dB

DL scheduler (TDS) PF (Proportional Fair)

DL scheduler (FDS) Improved PF (Proportional Fair scheduled)

UL scheduler (TDS) PF (Proportional Fair)

UL scheduler (FDS) Channel aware + Round Robin

MIMOSwitchMode dynamic MIMO 2x2 CL & SIMO

CQI‐Threshold‐upSM 15dB

CQI‐Threshold‐downDIV 10dB

RANK‐Threshold‐upSM 1,7

RANK‐Threshold‐downDIV 1,3

PL offset 0dB

DL Tx Power 0.8 / 0.4W

MIMO Compensation 0dB



__________________________________________________________________________________ PAGE 146

3x1 vs 3x2: Power per site / cell Equal power per site

Traffic Model Full Buffer

UE speed 3km/h

Average number of UEs per cell 3x1 10

Average number of UEs per cell 3x2 5

UL Tx Power 23dBm

UL PC mode Open loop power control

UL PC P0 ‐80dBm

simulation time 300s

The dynamic simulator inputs: real digital terrain map and real cellular network (3G) site locations17. RESULT 9: Discontinuous coverage of inner and outer cells with increase handoff is observed. Complementary to the results presented as RESULT 3 & 5 above coverage problem might appear in real life implementation and efficiency degradation can be observed.

Figure 115 Best server map for 3x1 and3x2 case

RESULT 10:

Throughput gains have been presented for UL on Figure 116 and for DL on Figure 117. Values are

given per sector in comparison to the case with no vertical sectorisation (3x1). The selected sectors in

real network topology have limited outer sector and concentration of users in inner cell. No

numerical threshold was setup and no algorithm for selecting sectors were used to determine site for

VS. For simulations have been used traffic model as described in Table 31.

17

As simulation results concerns product that is under development only limited outputs can be presented

innercell

innercell innercell

OUTERcell

OUTERcell

OUTERcell



__________________________________________________________________________________ PAGE 147

Figure 116 UL throughput gain for 31 most loaded sectors

Figure 117 DL throughput gain for 31 most loaded sectors

Average throughput gains based on received outputs on dynamic simulator are for UL: 79% for DL:

45% Details cell throughput gain per sector are aggregated in Table 32. There are sectors with

negative impact of VS (1 in UL and 2 in DL) due to increase interference level and low load of inner

cell. This case is observed when high building is close to the site and beam with high downtilts covers

only small area. Measurements presented in [72]. The vertical sectorisation feature performance is

also studied in [74].



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Table 32 Outputs for real network locations cluster 31 urban sites

Cell throughput

gains

UPLINK [%] -

10 38 97 56 53 37 54 31 43 82 61 87 58 51 103 94

avera

ge

DOWNLINK [%] 3 -3 -6 24 28 30 33 66 24 34 57 53 43 37 27 57

Cell throughput

gains

UPLINK [%] 62 85 93 83 111 123 72 120 97 132 89 91 80 120 150 79%

DOWNLINK [%] 33 25 104 35 37 73 41 85 63 42 63 67 55 88 82 45%



__________________________________________________________________________________ PAGE 149

Appendix G: Horizontal beam-steering measurements

Test of LTE prototype antenna was tested in far field in Camlez [38]. Calibration of test environment was done with horn antenna AL-2308-284 (17dBi gain). The free space losses, dish gain with cable losses were measured. Calibration was done for 2,661GHz. After calibration horn antenna has been replaced by prototype measured antenna. Figure 118 represents calibration configuration.

Figure 118 Calibration configuration for 2661MHzfrequency

The RRSI measurements have been collected for -180o to +180o by rotating the prototype antenna with step by 0.5o, 25 frequency points in range listed on Table 33, for 2 polarization at the time. On Figure 119 has been presented measurement configuration

Table 33 Measured band frequencies

Bottom Central Top

Rx [MHz] 2502.5 2535 2567.5 Prototype is antenna array with ability of beamforming in horizontal plane in the range of ±30o. The details of prototype design are covered by NDA and cannot be reviled. Measurements were done for azimuth 0 – the HPBW is approximately 50o and for azimuth -30o and + 30o where HPBW is reduced to 30deg in order to reduce sidelobes. Obtained antenna patter delivering realistic view for horizontal beamforming issues and confirmed simulated in V6S section expectation of sidelobes effect and physical limitation of the range of beam steering flexibility.



__________________________________________________________________________________ PAGE 150

Figure 119 Measurement configuration for 2502.5 – 2567.5MHz frequency

Figure 120 Horizontal beam-steering measured results for azimuth 0o



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Figure 121 Horizontal beam-steering measured results for azimuth -30o

Figure 122 Horizontal beam-steering measured results for azimuth +30o



__________________________________________________________________________________ PAGE 152



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