Development of Semi-Smart Antenna Technology - Ofcom | Stakeholders

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Antennas, propagation and radio systems Design, installation and commissioning

BSC Associates Ltd

Development of Semi-Smart Antenna Technology

Contract No: 830000081Queen Mary, University of London

Lucent Technologies (UK)BSC Associates Ltd

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BSC Associates Ltd

Summary of presentationIntroduction & “What’s a semi-smart antenna?” (20 mins)

Existing smart antenna solutions, their advantages & limitations(15 mins)

The process of cooperative load optimisation and the QM mobile network simulator (30 mins)

Prototype antenna hardware for semi-smart base stations (20 mins)

Market & Regulatory Analysis (30 mins)

Conclusions (5 mins)

Lunch + demonstration of semi-smart antenna hardware (60 mins)

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The Research Team

Queen Mary:Prof. Clive PariniDr Dong ChenDr John BighamDr Yasir Alfadhl

Lucent Technologies:Dr Louis SamuelDr Lester Ho

BSC Associates:Prof. Brian Collins

Antennas, propagation and radio systemsDesign, installation and commissioning

BSC Associates Ltd

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BSC Associates Ltd

Conventional Smart Antenna Technology

Smart antennas include a number of techniques that attempt to increase the system capacity by directing the “radiation pattern” towards the desired user to reduce interference.

Target user

Interfering user

Base station

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Fully Smart Antennas

•Combination of an array antenna with digital signal processing to transmit and receive in an adaptive spatially selective manner

•Good analogy is how your ears pick out and can focus on one conversation in a crowded room:-

•You hear the speakers signals through your ears (antennas).

•The sound arrives at each ear at a different time

•Your brain (signal processor) correlates the signals and computes the direction of arrival and then adds the signals from each ear in the correct phase to account for the different time of arrival

•By replacing the 2 ears (antennas) with say 8 - 12 antennas gives higher spatial resolution.

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LPF A/D

~

Desired signal

direction

LPF A/D

LPF A/D

LPF A/D

Interference or

multipath

signal direction

Amplitude and phase weights set to provide desired ‘Beam” in direction of signal and a null in the direction of the interference

Second channel can produce a second”beam”

Digital Beamformer (DBF)

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Key benefits:

Enhanced coverage through range extension, reducing the initial deployment cost to install a wireless system

Lower transmit power

Spatial separation among users allows sharing the same spectral resource

Improvement in the Link quality by mitigating the impact of multi-path or exploiting the diversity inherent in multi-path (e.g. MIMO)

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Factors preventing the adoption of this technology:

Requirement of real-time knowledge of the propagation characteristics of the radio channel

Positional tracking of individual users is required in order to point beams towards them

The complexity of smart antennas and their integration into cellular systems has proven to be a major drawback

Social and environmental concerns regarding the presence of multiple antennas in highly visible base stations

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Conventional Cellular Coverage…

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Excessively high traffic in one cell leads to lost calls…

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Excessively high traffic in one cell leads to lost calls…

Can youhelp me?

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…and with AI based negotiation the semi-smart base-station antenna patterns co-operate

“Hotspot” cell reduced in size

In the semi-smart antenna approach, the concept of adaptive beam-forming is simplified to dynamically changing cell shapes for balancing the traffic load over base stations

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Semi-Smart Antenna Technology

Key benefitsReactive to call traffic changingTreats clusters of users not individual usersUpdates every 30 secondsHigh capacityRetrofit to existing dumb base-stationsCan work in conjunction with dumb basestationsCan accommodate “portable” basestationsDifferent class (QoS) of users can be accommodated

“Hot-spot” cell reduced in size

Surrounding cells adjust co-operatively

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Typical simulator result:

location of the hot spot can be seen in thecentre of the region shown by the large number of blocked traffic (red dots)

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Effective real time algorithms for cooperation are key to the concept

Have developed negotiation based algorithm

Recently the“Bubble” algorithm which has elasticity built in

These cooperative algorithm do not depend on the air interface GSM, UMTS, WCDMA etc.

Core algorithm does not depend heavily on details of the antennatechnology

E.g. the number of elements and sectors directions

Not fully optimal, but need real time solutions

Global simulator developed to compare results

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Antenna Pattern Synthesis

The pattern synthesis we need here has few elements and highly shaped patterns with low angular accuracy low angular accuracy and low gain.and low gain.

Many complex synthesis methods have been developed. Here we investigate the use of optimisation algorithms in the synthesis process.

Currently we are employing an approach using case-base reasoning method linked with a Quasi-Newton optimisation algorithm to synthesise the patterns

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After negotiation with surrounding basestationsdesired coverage patterns are determined. Then….

Basic concept of the semi-smart antenna approach using case-based reasoning

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Shaped beam synthesis for smart antennas

Discrete desired coverage pattern

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Intelligent Control System Model

Mobile Cellular Network Simulator

Base Station Agent and Antenna Pattern Agent

Multi-agent System Infrastructure

MAS Directory Facilitator

Cellular Network Simulator

BaseStationAgent

AntennaAgent

Antenna Agent Base Station Agent

Communicator

Evaluator

Sensor

Executor

Negotiator LocalOptimizer ...

MAS Agent Management System

Executor

Communicator

PatternSynthesizer

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WCDMA Network Simulator

A Full-scale WCDMA network simulator has been development to evaluate the improvement on system capacity.

Different traffic scenarios are tested.

QMUL-smart antennas with online synthesiser are used.

Both uplink and downlink are simulated based on SINR value of users.

Interference from own and other cells is considered.

Power control is simulated iteratively

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Simulation Demo

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Typical simulator output

Ideal and synthesized patterns from negotiation results (coloureddots, diamonds and squares represent individual mobiles served by different base stations)

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Simulation Results (1)

0 50 100 150 200

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all-b

lock

ing

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e

Traffic Snapshots

Conventional cellular network Load-balancing (4-element antenna array) Load-balancing (cubic spline) Global optimization

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BSC Associates Ltd


0 20 40 60 80 100

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6800

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8400S

yste

m C

apac

ity

Snapshot

1- antenna element 2- antenna elements 4- antenna elements 6- antenna elements 8- antenna elements

6-sector, 0.5 wavelength spacing

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3-sector, 0.5 wavelength spacing

6300

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0 10 20 30 40 50 60 70 80 90 100

Traffic Snapshot

Syst

em C

apac

ity

2 elements3 elements

50,000 users

0.5 wavelength spacing between elements.

3 sectors

∴ 4-elements is the best option!

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Smart Antennas: Overview of Techniques and

Challenges

Ofcom funded project - No. 830000081

Queen Mary, University of LondonLucent Technologies (UK)

BSC Associates Ltd

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BSC Associates Ltd

Overview

Brief overview of smart antenna techniques

Some current implementations and applications

Challenges involved in deployment of smart antenna techniques

Summary

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Smart Antenna Systems

Smart antenna systems combines an antenna array with digital signal-processing capability to transmit and/or receive in an adaptive, spatially sensitive manner.

Smart antenna transceiver architecture

Simply put, these systems automatically change the directionality of its radiation patterns in response to its signal environment to increase the performance characteristics of a wireless system.

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Benefits of Smart Antennas

Two problems exist in typical mobile communications:

1.Multipath propagation due to the reflection of the transmitted signal by physical obstacles.

2.Co-channel interference due to the reuse of network resources (frequency, time) by multiple users.

Smart antennas increases capacity by mitigating interference and can improve link quality by combating/exploiting multipath propagation (when implemented with diversity techniques).

Base stationMobile 2

Mobile 1

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Benefits of Smart AntennasIncreased spectral efficiency

Spectrum can be expensive need to maximise usage/bandwidth.Interference reduction/mitigation increases the number of users sharing the same resources (e.g. frequency, codes).

Increased range/coverageIncreases average signal power at receive due to coherent combination of signals at all antenna elements (beamforming gain). Better area/base station and distance/base station.

Improved link quality/reliabilityDiversity gain achieved from receiving replicas of a signal through independently fading signal components.Highly probably one of signal components will not be in a deep fade reduces the effective fluctuation of the signal for more wire-like quality.

Lower power requirements and cost reductionsGain achieved from beamforming results in lower power consumption and amplifier cost.

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Smart Antenna Techniques

Fixed switched beam arraysUses a multiple fixed beams pointing in particular directions.These systems detect signal strength, choose from one of several predetermined, fixed beams, and switch from one beam to another as the mobile moves throughout the sector.

Direction finding arraysProcessing is used to determine the effective bearing of the signal and dynamically forms a beam in the determined direction and a null towards interferers.

Switched beam system coverage patterns (sectors)

Direction finding array coverage: Depiction of a main lobe extending toward a user, with a null directed

toward interferer

x1

x1

TreansmitterBeamforming

Receiver

Interferer

x1

x1

TreansmitterBeamforming

Receiver

Interferer

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BSC Associates Ltd

Smart Antenna Techniques

Receive diversity combining combines multiple signals antennas into a single improved signal. E.g. maximal ratio combining (MRC) and optimal combining.

Transmit space-time coding employs special modulation and coding schemes to improve link quality. E.g. space-time trellis and block coding (STTC, STBC).

Spatial multiplexing (MIMO) transmits different data bits via several independent (spatial) channels. E.g. BLAST.

Works when: (1) scattering is rich & (2) SINR is high.

Cellular systems are designed with minimal transmit power in mind, so condition (2) is not met at cell edges one obstacle for 3G.

But MIMO adopted in WLAN, because CSMA avoids interference, so received packets often have high SINR.

x1… xK

TransmitterSpace-Time

Coding

Receiver

x1… xK

Multiple-Input Single-Output (MISO)

x1… xK

TransmitterSpace-Time

Coding

Receiver

x1… xK

Multiple-Input Single-Output (MISO)

Transmitter

ReceiverDiversity

Combining

x1 x1

Single-Output Multiple-Output (SIMO)

Transmitter

ReceiverDiversity

Combining

x1 x1

Single-Output Multiple-Output (SIMO)

Transmitter Receiver

x1 x2 x3 x4

x1 x2 x3 x4

Multiple-Input Multiple-Output (MIMO)

Transmitter Receiver

x1 x2 x3 x4

x1 x2 x3 x4

Multiple-Input Multiple-Output (MIMO)

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Smart Antenna Techniques (cont.)

Space-division multiple access (SDMA)Creates spatially separate beams, directed at individual users. The users can share spectral resources because they are served by different beams provided by the antenna

Spatial filtering for interference reduction (SFIR)Receiver observes desired signal plus interference, combines signals from various paths and spatially filters out interfering signal.

x1

x2

x3

x1x2x3

TransmitterMulti-Beamforming

Receiver

Receiver

ReceiverConcept of an SDMA system

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BSC Associates Ltd

Smart Antenna Techniques (cont.)

Opportunistic beam forming takes advantage, rather than compensate fading (Vishwanath, Tse & Laroia).Random beamforming deliberately introduces artificial fluctuations in the channel SIR. Data then transmitted only to the best user.The mobiles completely oblivious to the existence of multiple transmit antennas.Requires sufficient number of users in the system, and a fair scheduling technique.

0 500 1000 1500 2000 2500 300080

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Sup

porta

ble

Rat

eUser 1

User 2

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porta

ble

Rat

e

User 1

User 2

Slow fading environment (after)

Slow fading environment (before)

Illustrative effect of the introduction of fluctuations in opportunistic beamforming

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BSC Associates Ltd

Deployment of Smart Antennas

TD-SCDMA standardisation places smart antennas as one of its key technologies.

TDD allows accurate channel state information to be easily obtainable for beamforming.CDMA+TDMA limits simultaneous users to 16 a timeslot, reducing complexity for beamforming.

Downlink space-time transmit diversity is part of current release of 3GPP for UMTS.

Also currently under standardisation in IEEE wireless LAN (802.11n) and MAN (802.16) .

Commercial WLAN solutions using MIMO already available, and deployments in PHS mobile network has been widespread.

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Challenges and Limitations of Smart Antennas

Business and cost issuesHigh cost and long lead time of upgrading existing equipmentStandardisation (e.g. in 3GPP) is in its early stages, and translation to products would take time.

Obtaining channel state informationFeedback from mobile takes overhead, estimated CSI inaccurate.Although not an issue with TDD systems (e.g. TD-SDCMA, PHS)

Cost effectiveness factor due to increased complexity

At the base station side: Improved antenna structures, cabling structures, efficient low-cost RF and DSP architectures.At the UE side: Separate RF chains required, more powerful DSP, physical size due to antenna spacings (17cm at 900Mhz, 7.5cm at 2GHz).

16 antennas mounted on laptop, showing physical size considerations

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BSC Associates Ltd

Challenges and Limitations (cont.)

Radio propagation environmentIn high scattering environment, variability due to slow and fastfading limits effectiveness of beamforming approaches.In low scattering environment, diversity techniques become less effective as uncorrelated signals are needed.

Physical consideration of base station antennasOptimum performance obtained with 4-6 elements at 0.5λ, resulting in wider antennas (300-450mm for UMTS, 700-1050mm for 900MHz)Heavier (more complex to install), higher windload (stronger towers)Visual profile (larger antennas, more cables, difficulty in concealment) can give rise to negative public response due to aesthetics and health concerns.

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BSC Associates Ltd

Summary

Benefits of smart antennas in enhancing spectral efficiency, coverage and link quality is obvious.

Promising deployments in mobile communications has been picking up, but remains relatively small.

Issues such as complexity and cost effectiveness remains major challenges.

Simpler, “semi-smart” techniques has large promise while these issues are resolved.

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Semi-smart antenna simulation study



BSC Associates Ltd

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Report on the results of simulation experiments …

with cooperative semi-smart and cooperative tilting antennas to provide enhanced QoS in WCDMA wireless networks

Compare semi-smart performance with conventional base stationsInvestigate the performance in the presence of non uniformterrainShow the feasibility of incorporating other optimisations such as real time dynamic sectorisationInvestigate capability to enhance QoS differentiation while still retaining relatively more bronze customersCompare cooperative cooperative real time tilting with semi-smart and conventional base stationsDemonstrate the uniformisation effect of shaping coverageIndicate gains from the flexibility

Robustness to changesReduce the need for network planning

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Cooperative coverage problem similar to multi-dimensional knapsack problem

problem is which is a NP-hard problem and does not yet have a universal algorithm.

The dual objective Increase capacityminimize powerand the complicated constraints make our problem even harder than MKP.

Explored new real time methods that can utilize the special characteristics of geographical load balancing problems

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Negotiation Process

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Bubble Oscillation Algorithm

Radial repulsion forceAttraction force

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Layering other constraints and optimisations …

Base algorithm does not depend heavily on details of the antenna technology

GSM, UMTS, WiMax, WiFithe number of elements and sectors directions These optimisations can be superimposed upon the basic requirements Not fully optimal, but need real time solutions

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Overlay sectorisation optimisation on the BOA

Balance load among different sectors subject to:Sector boundaries should not exceed the physical limit the given antenna system can achieveSector size should not exceed the physical limit the given antenna system can achieveThe central directions should keep as close as possible to the central directions of standard sector patterns

Real time optimisation solved by search

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Location of the software

E.g. in a RNC, or a server with a fast link to an RNCA simple arrangement evaluated in the SHUFFLE project used master RNC and other slave RNCs to manage inter-RNC boundaries

Evaluated the communication overheads of a centralised system and a distributed oneAnd this is also a possibility here

cooperative-enabled base stations could be added incrementally

without modification to other conventional base stations

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BSC Associates Ltd

WCDMA

Use WCDMA to evaluate (for definiteness)

many simulations (and tools) assume that the other-cell to own-cell interference ratio is a constant;

this cannot be assumed when there are hot spots or where antenna radiation patterns can change.

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BSC Associates Ltd

WCDMA simulator: What has been developed

Uses traffic snapshots

Admission Controlstandard wide-band power-based strategy is used for uplinkThe own cell interference is updated during each simulation iteration, whenever the subscription status changes.The other cell interference is updated after each iteration.

The soft and softer handover in the uplink is taken into consideration, while it is ignored in the downlink as the Site Selection Diversity Transmit (SSDT) soft-handover strategy is assumed there.

Power control is realized iteratively for each traffic snapshot.

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A test network

0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0 8,0 9,0

0,2 1,2 2,2 3,2 4,2 5,2 6,2 7,2 8,2 9,2

0,1 1,1 2,1 3,1 4,1 5,1 6,1 7,1 8,1 9,1

0,3 1,3 2,3 3,3 4,3 5,3 6,3 7,3 8,3 9,3

0,4 1,4 2,4 3,4 4,4 5,4 6,4 7,4 8,4 9,4

0,6 1,6 2,6 3,6 4,6 5,6 6,6 7,6 8,6 9,6

0,5 1,5 2,5 3,5 4,5 5,5 6,5 7,5 8,5 9,5

0,7 1,7 2,7 3,7 4,7 5,7 6,7 7,7 8,7 9,7

0,8 1,8 2,8 3,8 4,8 5,8 6,8 7,8 8,8 9,8

0,9 1,9 2,9 3,9 4,9 5,9 6,9 7,9 8,9 9,9

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Some results: Details of simulation

Each traffic snapshot contains 50, 000 users in the whole area, and all the users are uniformly distributed at the first snapshot;

One or more traffic hot-spots are forming from the first to the last snapshot;

Each hot-spots contains 1000 users, and the other users are always uniformly distributed in the whole area;

The locations of the users in hot spots follow normal distributions around the hot-spot centre. The mean value representing the location of the central point of each traffic hot-spot, is uniformly distributed with the minimum central distance of any two greaterthan 3r, where r is the cell radius, and the standard deviation 0:5r represents the size of each traffic hot-spot;

The active and idle time for each user has a negative exponential distribution. The mean values are 120 sec and 720 sec respectively.

One base station with 6 sectors is installed in the center of each cell.

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System Call Blocking rate for WCDMA network

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QoS – differentiation of services

differential grades of user service

e.g. gold, silver and bronze

Different “typical”types of traffic

Desired Cell Radiation Pattern

Users Served:23% Gold29% Silver6% Bronze

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Prioritisation

User Block Rate For Geographic Load Balancing(4000)

00.050.10.150.20.250.30.350.40.450.5

1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91

Traffic Snapshots

Block Rate

Gold

Silver

Bronze

Cooperative shaping ensures gold users do not get blocked or dropped

Results are for different mixes of G:S:B and types of traffic

All show capability

NB NO buffering NO forecasting

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Different Mixes of Traffic Types

Mix I all requests are 32 kb/sec all

Mix II 32 kb/sec 64 kb/sec 144 kb/sec ratio 1:1:1

Mix III 32 kb/sec 64 kb/sec 144 kb/sec ratio 6:3:1

Mix IV 32 kb/sec 64 kb/sec 144 kb/sec 384kb/sec ratio 1:1:1:1

Mix V 32 kb/sec 64 kb/sec 144 kb/sec 384kb/sec proportion 80% 10% 9% 1%

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Utility Function in Bubble Oscillation Algorithm

The original utility value of a single QC :

∑∑==

+⋅⎥⎦

⎤⎢⎣

⎡−⋅+=

M

m

Tm

N

jijjjii UARU

00)1()cos( θθ

∑=

−⋅+=N

jijjjii ARU

0

)cos( θθ

The modified utility value of a single QC :

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The “business model” used

The differentiated QoS utility of a single traffic unit is formulated as:

the traffic utility of traffic unit I

the user grade of the traffic unit ; in the simulations 3 for a gold user , 1 silver user and 0 bronze user.

the rate grade of the traffic unit i; numerically = maximum bit rate of traffic class/ 16 kbps, e.g. 144/16 = 9

irigTi RWGWU ⋅+⋅=

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Inclusion of information about the topography

Modified BOA to handle multiple perceptions

An extended BOA was developed and tested on data from Jersey

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Mapping from physical location to perceived location

Physical distance

Sig

nal s

treng

th

Cross sectionPerceived location

Forces now computed from powers

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Handling Multiple perceptions

Modified the BOA to handle this!

Real location

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Aircom Enterprise’s prediction of Pilot power map (carrier 1, with resolution of 10 m).

We work out a more accurate site-specific path loss model

Extracted data and placed in relational DBUsed to provide signal strength rather than an inverse power law

UMTS Pilot coverage map: Using Aircom’s data for Jersey

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Real Time Cooperative Tilting

There are totally 50,000 UE within the network and most of UEs are always moving.

10 hotspots form during the simulation and each has a population of 2,000 subscribers

so 40% of the subscribers are within hotspots at the end. The relative location of each MS within a hotspot follows a normal distribution with a standard deviation of half the cell radius.

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Real Time Cooperative Tilting

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Increase in handover rate

Although the cellular coverage is changing gradually according to the traffic changes,

extra user handovers are still the main side effect of concern when adopting such a scheme.

Some simulations for the handover rate for both uplink and downlink were performed using the same configuration for capacity and call-blocking rate simulations. The increments of handover rate is nearly a fixed small amount.

This is due to the constant moving speed of users in hot-spots andthe stableness of the bubble oscillation algorithm

it can almost reach the optimum cell size and shape according to the current traffic distribution.

The handover performance in the downlink is better than uplink, as soft-handover is not considered in the downlink.

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The uniformisation effect: evidence that……..

in the uplink, the other cell to own cell interference ratio is reduced and stabilised even when the traffic is not uniformSo network planning and optimisation (and simulation) for WCDMA networks

could be simplified or the need reducedbut still be accurate in complex traffic conditions If cooperative load balancing is performed

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Results(1) - Iother to Iown Ratio

The PDF of the Ratio for conventional and optimised networks with (a) uniform traffic, (b) 1 traffic hot-spot, (c) 10 traffic hot-spots and (d) 40 traffic hot-spots.

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A test network – BS can only move a quarter of distance to nearest BS

0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0 8,0 9,0

0,2 1,2 2,2 3,2 4,2 5,2 6,2 7,2 8,2 9,2

0,1 1,1 2,1 3,1 4,1 5,1 6,1 7,1 8,1 9,1

0,3 1,3 2,3 3,3 4,3 5,3 6,3 7,3 8,3 9,3

0,4 1,4 2,4 3,4 4,4 5,4 6,4 7,4 8,4 9,4

0,6 1,6 2,6 3,6 4,6 5,6 6,6 7,6 8,6 9,6

0,5 1,5 2,5 3,5 4,5 5,5 6,5 7,5 8,5 9,5

0,7 1,7 2,7 3,7 4,7 5,7 6,7 7,7 8,7 9,7

0,8 1,8 2,8 3,8 4,8 5,8 6,8 7,8 8,8 9,8

0,9 1,9 2,9 3,9 4,9 5,9 6,9 7,9 8,9 9,9

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Simulation results

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Simulation results

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Other technologies. E.g. SS

WiMAx Forum October 24th 2005 (modified)

Demand and priorities can change over

timeConstruction

site/emergency services

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Avoiding an area

HOLE

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Summary

A key to efficiency in wireless networks is flexibility,

but wireless networks are not as flexible as they could or should be.

Techniques described add to the efficiency through flexible from cooperative control of the physical layer

Have demonstrated simulation results that indicate the capability

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SEMI-SMART Antenna Implementation

Antenna design issues:Dynamic beam shapingCompact and efficient!Other requirements..

SimpleCost effectiveRobust: Wind load, etc.Direct replacement for dumb antenna

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Creating the antenna Patterns - a prototype

Phase shifters for Downtilt

Fine tuning

RF switches for 0, 90, 180, 270 degrees phase difference

Coarse tuning

VNA

Shuffle simulation

Desired pattern Excitation

Measured pattern

0 20 40 60 80 100 120 140 160 180-40

-35

-30

-25

-20

-15

-10

-5

0Amplitude taper and phase shift (1.28λ spacing)

Angle θ

Rel

ativ

e P

ower

dB

Ideal radiation patternmeasured radiation pattern

Configuration of QMUL-smart antenna prototype test system.

Ideal pattern and measured patterns.

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Semi-smart antenna implementation



BSC Associates Ltd

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Using Electronic down tilt to provide array element amplitude control

-40.0

-35.0

-30.0

-25.0

-20.0

-15.0

-10.0

-5.00

0.00

-20 -15 -10 -5 0 5 10 15 20

main beam of VDT antenna

5deg position,dB1deg position,dB9deg position,dB

patte

rn a

mpl

itude

,dB

elevation angle

Phase of antenna elements forming array is controlled to produce a phased array beam scan.

1 2 3 4 5 6 7 8 9 100

0.1

0.2

0.3

0.4

0.5

0.6

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0.9

1

Downtilt, degrees

Amplitude

Downtilt as a means of amplitude control

effective amplitude

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BSC Associates Ltd

Possible deployable solution: Elements of array conformal to a cylinder

Considering

2GHz0.5λ spacing between elements

3-sector antenna r ≈ 250 mm

6-sector antenna r ≈ 500 mm

r

r

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Cylindrical array implementation

•Planar array best for high gain beams

•Circular array best for complex shaped low gain beams

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120°

30°

15°

1

2

3

4

Power splitter Stepper motors Phase shifters

Equal lengths of

Inp

AttenuaPattern

Prototype antenna (Single sector)

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-20

-15

-10

-5

0

5

10

MeasuredSimulated

(a) (b)

Conventional basestation antenna element (Jaybeam)

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BSC Associates Ltd

The sector array

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BSC Associates Ltd

Typical desired azimuth pattern

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BSC Associates Ltd

The actual azimuth array element in a vertical array

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BSC Associates Ltd

So now have 2D array (shown as a planar array here for simplicity)

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BSC Associates Ltd

Using Electronic down tilt to provide array element amplitude control

-40.0

-35.0

-30.0

-25.0

-20.0

-15.0

-10.0

-5.00

0.00

-20 -15 -10 -5 0 5 10 15 20

main beam of VDT antenna

5deg position,dB1deg position,dB9deg position,dB

patte

rn a

mpl

itude

,dB

elevation angle

Phase of antenna elements forming array is controlled to produce a phased array beam scan.

1 2 3 4 5 6 7 8 9 100

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Downtilt, degrees

Amplitude

Downtilt as a means of amplitude control

effective amplitude

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BSC Associates Ltd

Simulated result using downtilt “amplitude” control

Array elements are excited with amplitude of 1.0 and phase of 0°, except in* central vertical array is assigned with ‘amplitude’ of 0.7.

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BSC Associates Ltd

Phase shifters

Phase shifter requirements:High powerContinuous or discreteLinear (no intermodulation products)

So far, the most appropriate solution is mechanical phase shift

RF in

RFout

RF in

MECHANICAL

MOVEMENT

DIELECTRIC SLAB

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BSC Associates Ltd

Non mechanical LINEAR phase shifters

A design of a Ferroelectric material phase shifter. The phase ofthe signal travelling along the microstrip transmission line canbe altered by applying a potential difference between the SRR sheet (1) and the ground plane (2).

(2) Metal ground Ferroelectric material Substrate (1) Ground sheet consisting of the SRR

Split Ring Resonator (SRR)

Microstrip line

Feeding ports

Substrate

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BSC Associates Ltd

Development of Semi-Smart Antenna Technology

Ofcom funded projectContract No: 830000081


BSC Associates Ltd

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BSC Associates Ltd

Economic aspects

Network operators are under great pressure on operating costs

They are very interested in new technology which will save money

They are not receptive of technologies which cannot reduce operating costs

Spectrum availability is an issue only in specific locations in the UK

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BSC Associates Ltd

Competing routes

Existing networks

RET antennas

EDGE HSDPA / HSUPA

SAICDAIC

TX Diversity4-branch diversity

Multiple RF headsDAS

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BSC Associates Ltd

Remote electrical tilt

Most antennas currently being installed in 3G networks are RET capable

Their availability is leading to network-wide adaptivity, with antenna tilts modified dynamically to meet coverage demands

Traffic measurement and control infrastructure will enable semi-smart solutions to be overlaid with minimum cost

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BSC Associates Ltd

Smart antenna trials

A number of 4-column systems have been tested in network service. They have shown real benefit, but

Networks are critical of:

Cost

Size and weight

Complexity

Reliability

Maintenance skill set

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BSC Associates Ltd

Radio system interface

Smart antennas operate more effectively in a TDD environment

GSM and W-CDMA generate high max/mean power ratios and require very linear HPAs

MCPAs are bulky, inefficient and expensive

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BSC Associates Ltd

A smart alternative

8 x 2W amplifiers providing the same eirp as 128W PA

Symmetrical benefits in up- and down-links

Higher antenna gains

Dynamic null steering

Increased spectral efficiency

Lower cost

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BSC Associates Ltd

Interference Nulling

Desired Signal 1 Desired Signal 2

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BSC Associates Ltd


Desired Signal 1 Lost Desired Signal 2 Lost

I/C=18dB I/C=15dB

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BSC Associates Ltd


Simple CDMA with a Single Antenna

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BSC Associates Ltd

Simple Beamforming


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BSC Associates Ltd



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BSC Associates Ltd

Beam Patterns

Many beam patterns suggests high levels of multipath during data rate tests

This multipath is exploited by adaptive antennas.

This multipath would severely degrade conventional systems.

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BSC Associates Ltd

Beamforming Results

Average Downlink beamforming gain was 21 dB

92% of Non Line Of Sight (NLOS) locations had a Downlink beamforming gain of 18dB or better

Distribution of CPE Results During Drive Testing

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

16 <=

x < 17

17 <= x

< 18

18 <=

x < 1

9

19 <=

x < 20

20 <= x

< 21

21 <= x

< 22

22 <=

x < 2

3

23 <=

x < 24

24 <= x

< 25

25 <=

x < 2

6

26 <=

x < 27

% o

f sam

ples

1 Average per Drive Site1 Sample per Sec at each site

Navini Beamforming Results from Drive Test

1 Average per Drive Site

1 Sample per Sec at each site

16 <= x < 17 0% 1%17 <= x < 18 0% 4%18 <= x < 19 5% 10%19 <= x < 20 18% 20%20 <= x < 21 14% 18%21 <= x < 22 41% 24%22 <= x < 23 18% 10%23 <= x < 24 5% 6%24 <= x < 25 0% 2%25 <= x < 26 0% 1%26 <= x < 27 0% 1%

Total 100% 97%Samples 22 3908Average 21.1 21.1

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BSC Associates Ltd

IntercellIntercell InterferenceInterference

Signal Co-ChannelInterference

Signal Co-channelInterference

BTS 1 BTS 2



Uplink Downlink

BTS 1 Receive BTS 2 Receive

BTS 1 BTS 2

Terminal 1 Receive Terminal 2 Receive

Signal

Co-channelInterference


Signal

Signal


Co-Channel Interference

Signal

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BSC Associates Ltd

Who is already doing this to earn their revenue?

Acknowledgements and thanks toBeijing Xinwei Telecom Technology, Inc.

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BSC Associates Ltd

Architecture

Structure: Circular Array、 Panel Array

Calibration: Space-coupling、Circuit-coupling

Beamforming: Digital Beam Forming

Adaptive Algorithms:

Optimum / Adaptive / DOA

Optimum : MMSE、LS、 SNR、ML；

Non-blind Adaptive: LMS、RLS；

Blind Adaptive: CM；

DOA: ESPRIT、MUSIC…

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BSC Associates Ltd

Circular arrays

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BSC Associates Ltd

Circular array: Tech spec

Freq.： 2010~2025 / 1880~1920 / 1785~1805Omni-Gain： 10.5dBi(L=1400mm)、 7.5dBi(L=700mm) 360°Single-Gain： 14.0dBi(L=1400mm)、11.0dBi(L=700mm) ~80°Max. Gain： 17.5dBi(L=1400mm)、14.5dBi(L=700mm) ~36°V. HPBW: 7° 、 14°VSWR: < 1.3Amp/Phase Offset： < 0.5dB / 5 °Omni-Pattern： +-1dBIsolation： > 23dBPreset downtilt： 3 °~ 9 °Max. Power： > 100W

Dimensions approx1300mm x 250mm φ

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BSC Associates Ltd

Omni pattern

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BSC Associates Ltd

Max gain pattern

Beam direction: 0°- 22.5°

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BSC Associates Ltd

Circular array: adaptive pattern

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BSC Associates Ltd

Panel arrays

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BSC Associates Ltd

Panel array: Tech Spec

Freq： 2010~2025 / 1880~1920 / 1785~1805Single Gain： 15 dBi (L=1200mm) 、 H. HPBW~110°Max. Gain： 23.0 dBi (L=1200mm) 、 H. HPBW~11°V. HPBW: 7°H. HPBW: 120°～ 11°(variable)120 °edge level: -6dB ～ -10dB (variable)VSWR: < 1.3Amp/Phase offset： +-0.5dB / 5 °Isolation： > 23dBF/B ratio： > 25dBPreset Downtilt： 3 °~ 9 °Max. Power： > 100W

Dimensions approx 1270 x 660mm

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BSC Associates Ltd

Panel array: Sector beam

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BSC Associates Ltd

Sector array: adaptive beam

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BSC Associates Ltd

Personal view

Smart antenna techniques have great potential and offer important advantages in:

Spectral efficiency

Range

Cost

But the system needs to be designed to exploit their capabilities

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BSC Associates Ltd

Current problems

Research work is too fragmented

Subjects are chosen for interest, not likelihood of commercial exploitation

Researchers are unfamiliar with current network practice

No common benchmarks for assessing proposals

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BSC Associates Ltd

Standards

The best systems require new standards

Costly and time-consuming to agree

Who will drive this is the result is reduced infrastructure costs?

Too late for 2G and 3G – both FDD

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BSC Associates Ltd

Semi-smart solutions

Protocol agnostic

Symmetrical up/downlink capacity improvement

Simple, high reliability hardware

Simple cross-layer control, can genuinely be added to existing mixed networks

Existing network-wide control protocols

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BSC Associates Ltd

Ownership model

Physical size of smart or semi-smart antennas suggest common ownership model for network hardware

Share hardware costs

Increase trunking gain in rural areas

Reduce environmental impact

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BSC Associates Ltd

Regulatory aspects

Network operators want to reduce operating costs

Increased range implies higher eirps

Keep-out zones will need extending

Public perception of large antenna arrays will be negative

Genuine radical infrastructure sharing is seen as a foggy area with regard to regulatory intentions

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BSC Associates Ltd

Perhaps…?

Future networks will employ:DAS systems in the citiesSmart antennas ?RET and semi-smart techniques in the outer suburbs Conventional antennas in the rural areasCommon base stationsTD/OFDM?

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BSC Associates Ltd

Conclusions (I)

There is clear evidence that the fully smart antenna can offer considerable capacity improvement - but at the expense of radical hardware infrastructure changes - this is likely to be a future generation solution.

The semi-smart technology can offer a shorter term solution to capacity improvement in 3G systems and offers of order 20% capacity improvements.

With the recent adoption of down-tilt protocols in current 3G, the essential “software hooks” for semi-smart are now in place.

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BSC Associates Ltd

Conclusions (II)The size of base-station antennas will always be an issue for smart antennas. The proposed semi-smart solution offers a tower compatible low visual impact solution.

Full advantage (in terms of: capacity, infrastructure costs, costs per bit, spectrum efficiency, environmental impact) of both smart and semi-smart technologies will only be achieved with a radical change to a shared infrastructure -which can only be lead by Government.

We have developed a sophisticated network simulator that is capable of quantitative comparisons for smart antenna solutions (smart, semi-smart, mesh, WLAN, etc.)

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BSC Associates Ltd

Demo of semi-smart antenna prototype

120°

30°

15°

1

2

3

4

Power splitter Stepper motorsPhase shifters

Equal lengths of

Inp

Attenua

Inte

rfac

e ci

rcui

t

Pattern

Documents

Development of Semi-Smart Antenna Technology - Ofcom | Stakeholders