D2.3 Definition of reference scenarios, overall …...D2.3: Definition of reference scenarios, overall system architectures, research challenges, requirements and KPIs Date: 01/02/2016

SANSA-645047

D2.3

D2.3

Definition of reference scenarios, overall system architectures, research challenges, requirements and

KPIs

Grant Agreement nº: 645047

Project Acronym: SANSA

Project Title: Shared Access Terrestrial-Satellite Backhaul

Network enabled by Smart Antennas

Contractual delivery date: 01/02/2016

Actual delivery date: 01/02/2016

Contributing WP WP2

Dissemination level: Public

Editors: AVA

Contributors: CTTC, TAS, ULUX, AIT, OTE

Abstract: This deliverable contains the outcomes of Task 2.3 and Task 2.4. It will specify the scenarios and

network architectures covered in SANSA project as well as the technological requirements and

KPIs.

D2.3: Definition of reference scenarios, overall system architectures, research challenges,

requirements and KPIs Date: 01/02/2016

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Document History

Version Date Editor Modification 0.0 22/06/2015 AVA Document creation and Table of Contents

0.1 09/09/2015 AVA Initial input from AVA regarding the overall scenario

selection strategy, the rural scenarios, specific

network elements and some examples of KPIs as

well as initial input regarding end to end system

architecture from CTTC

0.2 29/09/2015 AVA CTTC input regarding urban scenario and research

challenges, OTE input on the requirements and the

research challenges, AVA input on research

challenges and system architecture requirements.

KPI inputs by TASE and OTE

0.3 -0.5 From

29/09/2015

to

18/01/2016

AVA Various inputs from AVA, ULUX, CTTC, OTE, TAS &

OTE.

0.6 18/01/2016 AVA Document Ready for QA

0.7 25/01/2016 AVA QA by AIT

0.8 29/01/2016 AVA QA by AVA

0.9 29/01/2016 AVA QA documents addressed

1.0 29/01/2016 AVA Final document ready for submission



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Contributors

Name Company Contributions include

Georgios Ziaragkas AVA All document

Georgia Poziopoulou AVA All document

Simon Watts AVA Quality Assurance

George Agapiou OTE Chapters 3, 5

Ioanna Papafili OTE Chapter 6

Pantelis Argyrokastritis OTE Chapters 3, 5

Panagiotis Matzoros OTE Chapters 3, 5

Xavier Artiga Campos CTTC Document Review

Miguel Ángel Vázquez CTTC Chapters 2, 3 and 6

Jose Núñez Martinez CTTC Chapter 4, 5

Musbah Shaat CTTC Chapters 2, 3

Symeon Chatzinotas ULUX Chapter 3, 5, 6

Dimitrios Christopoulos ULUX Chapter 3, 5, 6

Shree Krishna Sharma ULUX Chapter 3, 5, 6

Christos Tsinos ULUX Chapter 3, 5, 6

Isaac Moreno TASE Chapters 4, 6

Dimitris Ntaikos AIT Chapters 2, 3, 4

Kostas Voulgaris AIT Quality Assurance



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Table of Contents

List of Tables ......................................................................................................................................... 11

List of Acronyms .................................................................................................................................... 12

Executive Summary ............................................................................................................................... 15

1. Introduction .................................................................................................................................. 16

2. SANSA use cases ........................................................................................................................... 18

2.1 Scope ..................................................................................................................................... 18

2.2 SANSA selected use cases ..................................................................................................... 19

2.2.1 Radio link failure ............................................................................................................. 19

2.2.2 Radio link congestion ...................................................................................................... 22

2.2.3 New node deployment/incorporation ........................................................................... 25

2.2.4 CDN integration ............................................................................................................... 25

2.2.4.1 Satellite fed cache CDN ................................................................................................. 25

2.2.4.2 Cache fed through satellite and terrestrial link ............................................................ 26

2.2.5 Remote cell connectivity ................................................................................................. 27

2.2.5.1 Standalone cell .............................................................................................................. 27

2.2.5.2 Moving base station ...................................................................................................... 27

2.3 Relation of Event periodicity to the Selected Use-cases ...................................................... 29

2.3.1 Periodic-occurring events ............................................................................................... 29

2.3.2 Semi-periodic events ....................................................................................................... 30

2.3.3 Rarely repeated events ................................................................................................... 31

2.3.4 Seasonality ....................................................................................................................... 32

3. SANSA Scenario Definition ............................................................................................................ 33

3.1 Overall strategy ..................................................................................................................... 33

3.2 Strategy for designing and implementing a terrestrial backhaul system ............................. 35

3.3 SANSA selected scenarios ..................................................................................................... 36

3.3.1 Rural case ...................................................................................................................... 37

3.3.1.1 Rural Scenario #1 .......................................................................................................... 37



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3.3.1.2 Rural Scenario #2 .......................................................................................................... 37

3.3.2 Urban Case .................................................................................................................... 38

3.3.2.1 Urban Scenario #1 ......................................................................................................... 39

3.3.2.2 Urban Scenario #2 ......................................................................................................... 39

3.3.2.3 Urban Scenario #3 ......................................................................................................... 40

3.3.3 Moving base station scenario ....................................................................................... 40

3.4 Scenarios General Characteristics ......................................................................................... 42

3.4.1 Frequency bands ........................................................................................................... 42

3.4.2 Spectrum sharing between different MNO .................................................................. 43

3.4.3 Standards ...................................................................................................................... 44

3.4.3.1 Terrestrial air interface ................................................................................................. 44

3.4.3.2 Satellite air interface ..................................................................................................... 44

3.4.4 Regulation ......................................................................................................................... 45

3.5 Nodes distribution and generated traffic ............................................................................. 46

3.5.1 Satellite user terminals deployment ............................................................................. 46

3.5.2 Macrocell deployments ................................................................................................ 47

3.5.2.1 Urban scenario .............................................................................................................. 47

3.5.2.2 Rural scenario................................................................................................................ 48

3.5.2.3 Projected scenario for a 5G network ............................................................................ 49

3.5.3 Satellite and terrestrial content delivery traffic profile ................................................ 50

3.6 Interference landscape ......................................................................................................... 50

3.6.1 Intra-system interference ............................................................................................. 51

3.6.1.1 Interference between satellite and terrestrial links ..................................................... 51

3.6.1.2 Terrestrial to terrestrial link .......................................................................................... 52

3.6.2 Intersystem interference .............................................................................................. 52

3.7 Benchmarking topologies ..................................................................................................... 52

3.7.1 Rural topologies ............................................................................................................ 52

3.7.1.1 Topology Example: Helsinki .......................................................................................... 53



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3.7.1.2 Benchmark SINR distribution ........................................................................................ 56

3.7.1.3 SINR and interference analysis: Aggressive Frequency Reuse ...................................... 56

3.7.1.4 Terrestrial to Satellite User Terminal ............................................................................ 59

3.7.1.5 Satellite User Terminal to Terrestrial ............................................................................ 61

3.7.2 Urban topologies: The Vienna case .............................................................................. 63

3.7.2.1 Methodology ..................................................................................................................... 63

3.7.2.2 Topology ........................................................................................................................ 63

3.7.2.3 Interference analysis ..................................................................................................... 66

3.7.2.3.1 Methodology ......................................................................................................... 66

3.7.2.3.2 Case 1: Co-located microwave links ...................................................................... 67

3.7.2.3.3 Case 2: Terrestrial Links ........................................................................................ 68

3.7.2.3.4 Case 3: Satellite user terminal to terrestrial node ................................................ 69

3.7.2.3.5 Case 4: Terrestrial node to satellite ...................................................................... 70

3.7.2.3.6 Case 5: Terrestrial node to satellite user terminal ................................................ 71

3.7.2.3.7 Case 6: Satellite to terrestrial node ...................................................................... 72

3.7.3 Moving Base Station ..................................................................................................... 73

3.7.3.1 Fading due to Reflection of the Signal from the Sea Surface ....................................... 74

4. Definition of end-to-end SANSA Architecture .............................................................................. 78

4.1 Scope ..................................................................................................................................... 78

4.2 SANSA End-to-end System Architecture ............................................................................... 78

4.3 SANSA Transport Architecture .............................................................................................. 80

4.4 Intelligent Backhaul Node (iBN) Architecture ....................................................................... 81

4.5 Hybrid Network Manager (HNM) Architecture .................................................................... 82

4.6 Moving Base Station Architecture ........................................................................................ 83

5. Definition of Key Performance Indicators ..................................................................................... 84

5.1 Objectives.............................................................................................................................. 84

5.2 End user QoS requirements per service type ....................................................................... 84

5.3 Definition of end-to-end KPIs................................................................................................ 89



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5.3.1 Aggregated throughput ................................................................................................ 89

5.3.2 Backhaul network resiliency ......................................................................................... 89

5.3.3 Delay ............................................................................................................................. 90

5.3.4 Spectrum efficiency....................................................................................................... 91

5.3.5 Energy efficiency ........................................................................................................... 91

5.3.6 Population coverage ..................................................................................................... 91

5.4 KPIs and targets .................................................................................................................... 94

6. Identification of Research Challenges ........................................................................................... 95

6.1 Specific challenges associated with SANSA integrated terrestrial and satellite backhaul

node 95

6.1.1 Efficient allocation and management of resources in terms of cost and energy ......... 95

6.1.2 Investigation of handover capabilities between terrestrial and satellite backhaul

nodes 95

6.1.3 Interoperability of the iBN ............................................................................................ 95

6.1.4 Components design ...................................................................................................... 96

6.1.5 Traffic classification ....................................................................................................... 96

6.1.6 iBN interfaces with satellite and terrestrial links .......................................................... 96

6.1.7 iBN monitoring performance ........................................................................................ 96

6.2 Specific challenges associated with SANSA smart antennas ................................................ 97

6.2.1 Transceiver architectures .............................................................................................. 97

6.2.2 Angle Coverage ............................................................................................................. 98

6.3 Specific challenges associated with Hybrid Network Management ..................................... 98

6.3.1 Configuration management .......................................................................................... 98

6.3.1.1 Terrestrial system configuration ............................................................................... 98

6.3.1.2 Satellite system configuration .................................................................................. 99

6.3.2 Frequency plan management ....................................................................................... 99

6.3.2.1 Interference management ........................................................................................ 99

6.3.3 Fault management ........................................................................................................ 99

6.3.4 Performance management ......................................................................................... 100



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6.3.5 Network management (topologies) ............................................................................ 100

6.3.6 Interface with the core network (EPC)........................................................................ 101

6.3.7 SANSA CDN use cases ................................................................................................. 101

6.3.8 Mobility management ................................................................................................. 101

6.3.9 Security management ................................................................................................. 101

6.4 Specific challenges associated with spectrum sharing ....................................................... 101

6.4.1 Spectrum awareness techniques ................................................................................ 102

6.4.1.1 Spectrum Sensing .................................................................................................... 102

6.4.1.2 Spectrum Cartography ............................................................................................ 103

6.4.1.3 Spectrum awareness through regulatory databases .............................................. 104

6.4.2 Spectrum exploitation techniques .............................................................................. 106

6.4.2.1 Interference mitigation techniques ........................................................................ 106

6.4.2.2 Cognitive beamforming........................................................................................... 106

6.4.2.2.1 Cognitive Interference Alignment ....................................................................... 108

6.4.2.2.2 Cognitive Zone .................................................................................................... 108

6.4.2.3 Optimization of spectrum and radio resources ...................................................... 110

6.5 Specific challenges associated with integrated backhaul service delivery ......................... 111

6.5.1 Mobile terrestrial operator lead ............................................................................... 111

6.5.2 Hybrid Terrestrial Satellite Operator Service .............................................................. 112

6.5.3 Satellite operator service ............................................................................................ 113

7. Conclusions ................................................................................................................................. 115

8. References .................................................................................................................................. 117

A. Appendix ..................................................................................................................................... 122

1. Notations in Table 3-11 ........................................................................................................... 122

2. Satellite Link Budget................................................................................................................ 122

3. Terrestrial to terrestrial .......................................................................................................... 125

4. 18 GHz Link Budget (CTTC) ...................................................................................................... 126



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List of Figures

Figure 1-1: WP2 work plan .................................................................................................................... 16

Figure 2-1: Radio link topology before failures ..................................................................................... 21

Figure 2-2: Radio link failures events and solutions ............................................................................. 22

Figure 2-3: Congestion use case for the rural scenario ........................................................................ 25

Figure 2-4: Satellite fed CDN cache ....................................................................................................... 26

Figure 2-5: CDN cache fed through satellite and terrestrial connection .............................................. 26

Figure 2-6: Remote cell connectivity – Standalone cell ........................................................................ 27

Figure 2-7: Moving platform as a remote cell....................................................................................... 28

Figure 2-8: Moving platform facilitating the backhauling of a remote cell .......................................... 29

Figure 2-9: Periodic occurring events ................................................................................................... 30

Figure 2-10: Semi-periodic occurring events ........................................................................................ 31

Figure 2-11: Rarely repeated events ..................................................................................................... 32

Figure 3-1: SANSA scenarios characterization ...................................................................................... 33

Figure 3-2: Scenario selection strategy matrix example ....................................................................... 35

Figure 3-3: Moving base station scenario ............................................................................................. 42

Figure 3-4: Maximum available bandwidth for uncoordinated FSS stations based on CEPT

implementations [1] ............................................................................................................................. 43

Figure 3-5: Traffic analysis for urban scenario ...................................................................................... 48

Figure 3-6: Traffic analysis for rural scenario ........................................................................................ 49

Figure 3-7: 5G network consisting of a number of small cells .............................................................. 49

Figure 3-8: Zipf law ................................................................................................................................ 50

Figure 3-9: Interference landscape in the SANSA system ..................................................................... 52

Figure 3-10: Example backhaul topology obtained from the Finnish 28 GHz database, Helsinki. ....... 53

Figure 3-11: Benchmark SINR distribution of the coordinated frequency plan in Table 3-11.............. 56

Figure 3-12: SINR distribution of the links with aggressive frequency reuse ....................................... 58

Figure 3-13: Distribution of the required number of nulls with aggressive frequency reuse .............. 59

Figure 3-14: Aggregate Interference on the satellite terminals due to terrestrial transmissions ........ 60

Figure 3-15: SINR of the satellite terminals .......................................................................................... 61

Figure 3-16: Distribution of the number of nulls per link during uplink ............................................... 62

Figure 3-17: Network Topology for urban deployments ...................................................................... 64

Figure 3-18: Network Topology over Google Earth picture. ................................................................. 65

Figure 3-19: Tower details .................................................................................................................... 65

Figure 3-20: Stadium details ................................................................................................................. 66

Figure 3-21: Antenna discrimination angle ........................................................................................... 67

Figure 3-22: Interference analysis Case 1 ............................................................................................. 68

Figure 3-23: Interference analysis Case 2 ............................................................................................. 68



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Figure 3-24: Case 3 interference at 28 GHz .......................................................................................... 70




Figure 3-28: Cruise ship topology ......................................................................................................... 74

Figure 4-1: SANSA System Architecture ................................................................................................ 79

Figure 4-2: Representation of the iBN components ............................................................................. 81

Figure 4-3: Representation of the HNM functions ............................................................................... 82

Figure 4-4: Moving base station architecture ....................................................................................... 83

Figure 5-1: Model for user-centric QoS categories [14] ....................................................................... 87

Figure 5-2: Avanti coverage over the EU [16] ....................................................................................... 92

Figure 6-1: Example of spectrum cartography.................................................................................... 105

Figure 6-2: Classification of Interference mitigation approaches ....................................................... 106

Figure 6-3: Terrestrial Operator Lead ................................................................................................. 112

Figure 6-4: Hybrid terrestrial satellite operator network ................................................................... 113

Figure 6-5: Satellite lead service ......................................................................................................... 114

Figure A-1: Location of the satellite terminal for point-to-point link budget ..................................... 123

Figure A-3: Details for the best performing MODCOD in the satellite link budget ............................ 124

Figure A-3: Terrestrial link budget for 1 Km distance at 18 GHz......................................................... 127

Figure A-4: Terrestrial link budget for 5 Km distance at 18 GHz......................................................... 128



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List of Tables

Table 2-1: Link failure events description and responses ..................................................................... 20

Table 2-2: Congestions events description and responses ................................................................... 23

Table 3-1: Selected scenarios on the scenario selection strategy matrix ............................................. 36

Table 3-2: Rural scenario #1 on scenario selection strategy matrix ..................................................... 37

Table 3-3: Rural scenario #2 on scenario selection strategy matrix ..................................................... 38

Table 3-4: Urban scenario #1 on scenario selection strategy matrix ................................................... 39



Table 3-7: Moving base station scenario on scenario selection strategy matrix .................................. 41

Table 3-8: Urban users’ traffic profile ................................................................................................... 47

Table 3-9: Rural users’ traffic profile .................................................................................................... 48

Table 3-10: Projected scenario for a 5G network (networks.nokia.com) ............................................. 49

Table 3-11: Detailed information of each link ...................................................................................... 54

Table 3-12: The location of nodes......................................................................................................... 55

Table 3-13: Connectivity matrix ............................................................................................................ 55

Table 3-14: Simulation parameters for uplink ...................................................................................... 62

Table 3-15: Interference data for Case 3 interference analysis ............................................................ 69

Table 3-16: Interference data for case 4 interference analysis ............................................................ 70

Table 3-17: Interference data for case 5 interference analysis ............................................................ 71

Table 3-18: Interference data for Case 6 interference analysis ............................................................ 72

Table 5-1: Performance targets for audio, video and data applications [14] ....................................... 87

Table 5-2: Avanti Hylas 1 and Hylas 2 EU coverage .............................................................................. 92

Table 5-3: System end-to-end KPIs ....................................................................................................... 94

Table A-1: Directional Antennas (linear polarization) from 24.25 GHz to 30 GHz, types DN1 to DN5

............................................................................................................................................................ 125

Table A-2: SINR values of the different sub-scenarios ........................................................................ 125

Table A-3: Interference power levels .................................................................................................. 126

Table A-4: Parameters for the 18 GHz terrestrial link budget ............................................................ 126

Table A-5: Terrestrial link budget ....................................................................................................... 129



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List of Acronyms

ADC Analog-to-Digital Converter

AP Application Protocol

ASIC Application Specific Integrated Circuit

BATS Broadband Access via integrated Terrestrial and Satellite systems

BN Backhaul Node

BS Base Station

BSS Business Support System

CAPEX Capital Expenditure

CDN Content Delivery Network

CS Compressive Sensing

CSI Channel State Information

CZ Cognitive Zone

DL Downlink

DoA Direction of Arrival

DSCP Differentiated Services Code Point

DVB-S Digital Video Broadcasting – Satellite

EC European Commission

EIRP Effective Isotropic Radiated Power

eNB eNodeB

EPC Evolved Packet Core

ETSI European Telecommunications Standards Institute

EU European Union

FDD Frequency Division Duplex

FPGA Field-Programmable Gate Array

FSS Fixed Satellite Service

FWD Forward (channel)

GEO Geostationary Orbit

GTP-U GPRS Tunnelling Protocol User Plane

HDFSS High-Density applications in the Fixed-Satellite Service

HeNB Home eNodeB

HNM Hybrid Network Manager

HSS Home Subscriber Server



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HTS High Throughput Satellite

IA Interference Alignment

iBN Intelligent Backhaul Node

IPsec IP Security

KPI Key Performance Indicator

LAA License Assisted Access

LoS Line of Sight

LSA License Spectrum Access

LSAS Large Scale Antenna Systems

LTE Long Term Evolution

MBBS Macrocell Backhaul Base Station

MBS Mobile Base Station

MCN Mobile Core Network

MME Mobile Management Entity

MNO Mobile Network Operator

MODCOD Modulation Coding

NG HTS Next Generation High Throughput Satellite

NMS Network Management System

O&M Operation & Maintenance

OFDMA Orthogonal Frequency Division Multiple Access

OPEX Operational Expenditure

OSS Operations Support System

PDN-GW Packet Data Network Gateway

PLR Packet Loss Ratio

PtMP Point-to-MultiPoint

PtP Point-to-Point

QoS Quality of Service

R&D Research & Development

RAN Radio Access Network

REM Radio Environment Map

RF Radio Frequency

RTN Return (channel)

SA Smart Antenna

S-GW Serving Gateway

SINR Signal to Interference plus Noise Ratio



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SMS Short Messaging Service

SNR Signal to Noise Ratio

SoTA State of the Art

TCO Total Cost of Ownership

TDD Time Division Duplex

TDMA Time Division Multiple Access

TNA Transport Network Architecture

UE User Equipment

UL Uplink

UWB Ultra Wide Band

VSAT Very Small Aperture Terminal

Wi-Fi Wireless Fidelity

WP Work Package

WSS Wideband Spectrum Sensing



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Executive Summary

This is Deliverable D2.3 of the SANSA “Shared Access Terrestrial-Satellite Backhaul Network enabled

by Smart Antennas” project which documents the outcome of Task 2.3 “Scenario selection and

network architecture definition” and Task 2.4 “Definition of Key Performance Indicators. The

objective of this deliverable is to define the appropriate use cases, with its possible assumptions and

constraints, and to define and form the overall system architecture in an end-to-end fashion. It also

aims at looking at the technical challenges to be addressed when designing our proposed solutions

and how they are improving the current state-of-the-art. It is also defining the Key Performance

Indicators to be used while evaluating, comparing and selecting among different technological

solutions. The material documented in D2.3 will allow the SANSA consortium to define the reference

scenarios, the overall system architectures, the research challenges/requirements and the Key

Performance Indicators.

In this report after identifying the use cases, the most relevant scenarios are being selected and the

topologies to be used to further research the interference landscape, network architectures and the

design of the key enabling components are provided. End to end system architecture is also

provided along with the KPIs that will be used to evaluate the novelties and the performance

enhancement that SANSA introduces. Last but not least, all research challenges associated with

SANSA are presented.



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1. Introduction

The objective of this document is to define the use cases and scenarios, as well as the end-to-end

system architecture and the end-to-end KPIs that will be used to assess the SANSA solution. Lastly,

the technical challenges that will be studied in the following WPs will be specified.

This deliverable is the output of the work done under Tasks 2.3 and 2.4 of WP2. WP2 aims to define

the scenarios and network architectures that will be used in SANSA as well as the Key Performance

Indicators (KPIs) for evaluating the proposed SANSA solution. Figure 1-1 illustrates how Tasks 2.3

and 2.4 fit within the WP2 work plan.

Figure 1-1: WP2 work plan

This remainder of this deliverable is divided into six chapters that are organised as follows:

Chapter 2 discusses the SANSA use cases and explains why they are relevant to the project.

These are radio link failure and/or congestion, new node deployment, CDN integration in the

network and remote cell connectivity which can refer either to a standalone cell or a moving

base station.

Chapter 3 presents the 5-axis scenario definition strategy and fully defines the SANSA scenarios.

The strategy followed takes into consideration the type of deployment, the CDN integration, the

type of spectrum sharing and the terrestrial and satellite link characteristics to create the 6

scenarios which will be used from the following WPs to further investigate the SANSA solution.

Additionally, this chapter summarises the common general scenario characteristics such as the

air interfaces and spectrum licenses used, the strategy for selecting the nodes that will be

equipped with a satellite terminal and traffic forecasting at the macrocell and CDN level. Lastly,

the interference landscape for the SANSA network is presented along with benchmarking

topologies for the rural, urban and moving base station scenarios with a focus on the

interference analysis. These benchmark topologies provide the basis of the interference



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mitigation techniques that will be studied in WP3.

Chapter 4 defines the SANSA end-to-end architecture including the transport and key enabling

components architecture.

Chapter 5 reviews the objectives of the project and sets appropriate end-to-end KPIs which will

be used to evaluate the outcomes of the project. For every KPI a definition, the method of

evaluation, the target value and a motivation with clear links to the project objectives is

provided.

Chapter 6 identifies the research challenges that will drive the work in subsequent WPs. The

main thematic categories presented are challenges associated with the integration of the

terrestrial and satellite backhaul nodes, the key enabling components, the spectrum sharing

and the integrated backhaul service delivery.

Chapter 7 draws conclusions from the analysis of the preceding chapters.



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2. SANSA use cases

2.1 Scope SANSA project was stimulated by a set of existing problems in the current mobile backhauling

networks. In order to solve these problems and design an enhanced network with improved

backhauling capabilities, a set of objectives has been proposed. These objectives are challenging

current network designs and try to solve the problems they are encountering. They are also relevant

and according to the targets set by 5G. Within the frame of the solutions design, a number of use

cases have been identified in order to properly define the problems and create the appropriate

framework, the scenarios, in which a number of problems are addressed in a structured manner. In

order to quantify our scenarios and to be able to simulate problems and test solutions, instances of a

part of the network under a specific scenario will be used as the reference topology.

As already mentioned in the previous paragraph and throughout the document the terms use case,

scenario, topology will be used. At this point it is very important to clearly define the meaning of

each of the terms in order to avoid confusions and present clearly the way scenario definition is

structured.

Use case is the term used to describe a problem created or a challenge that has to be addressed

within a network. In SANSA the use cases are resiliency, offloading, new node development, CDN

integration and remote cell connectivity. It is worth mentioning here that the periodicity in which

events occur is really important to define the scenarios properly.

Scenario is a specific situation, where one or more of the use cases have to be addressed. The main

separation is into three main categories rural, urban and moving base station. Within each of the

main categories there are sub-scenarios, which are direct results of changes in the scenario

parameters (e.g. the use of CDN or not in a rural environment is a variable that can change the rural

scenario).

Topology is the term used to define an instantiation of a part of a network. It will be used to

demonstrate the new features and capabilities that SANSA will offer. Interference analysis, hybrid

network management and optimization, satellite integration, smart antenna capabilities, energy

efficiency and re-configurability will be demonstrated on benchmark topologies but the results can

be extrapolated and used to different network topologies as SANSA is not aiming at providing a

network oriented solution, but a solution that can be adopted by any network and any operator.

Subsequent WPs will work taking into consideration as reference the scenarios and the topologies as

they will be defined within this deliverable.



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2.2 SANSA selected use cases

2.2.1 Radio link failure One of the main SANSA characteristics is the ability to offer resilience to cases of link failure. The

satellite connectivity and the use of the smart antennas with the help of the Hybrid Network

Manager add flexibility to backhauling networks by either providing an alternative route, through

satellite, where satellite terminals are available to the user or through an alternative terrestrial link

when another node is available with the use of a smart antenna with steerable beams.

In Figure 2-1 some examples of link failure events and how SANSA system provides resilience to the

affected links are presented:

Event 1: Link A-B fails. Traffic from node A cannot access the core.

Event 2: Link D-G fails. Traffic should follow the D-E-F-G path to access the core. This creates

congestion to the rest of the nodes.

Event 3: Node G fails. No access to the core.

Event 4: Link F-I fails. Traffic from nodes H, I and J cannot access the core.

Event 5: Link H-I fails. Node H cannot access the core.

The above mentioned events are causing network failures. SANSA network is designed in a manner

to offer resilience for link failures. The system response as illustrated in Figure 2-2 to each of the

events is as follows:

Event 1: Link A-B fails. The satellite terminal on node A redirects traffic to the core network

through the satellite network.

Event 2: Link D-G fails. This link is part of a ring topology that reroutes traffic through the

alternative way. The novelty with SANSA is that the traffic that could create moderate or

heavy congestion to the system can be partially offloaded at node E, with the help of the

iBN, according to the traffic classification rules that have already been set.

Event 3: Node G fails. Node E acts as a backup aggregator, routing the traffic through the

satellite network to the core or directly to the internet, depending on the selected service

model.

Event 4: Link F-I fails. Again the VSAT terminal at node F is used as a backup connection to

the core or to the internet, routing traffic from all affected nodes (H, I, J).

Event 5: Link H-I fails. Node H cannot access the core but the steerable smart antenna

directs its beam from I to J and establishes a new terrestrial link. The increased traffic can be



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offloaded through the satellite connection at node I.

The events description and responses are presented in Table 2-1.

Table 2-1: Link failure events description and responses

Event Failure Description Response

1 Link A-B Traffic from node A cannot

access the core.

The satellite terminal on node A redirects

traffic to the core network through the

satellite network.

2 Link D-G Traffic should follow the D-E-

F-G path to access the core.

This creates congestion to the

rest of the nodes.

This link is part of a ring topology that

reroutes traffic through the alternative way.

The novelty with SANSA is that the traffic

that could create moderate or heavy

congestion to the system can be partially

offloaded at node E, with the help of the

iBN, according to the traffic classification

rules that have already been set.

3 Node G No access to the core. Node E acts as a backup aggregator, routing

the traffic through the satellite network to

the core or directly to the internet,

depending on the selected service model.

4 Link F-I Traffic from nodes H, I and J

cannot access the core.

Again the VSAT terminal at node F is used

as a backup connection to the core or to the

internet, routing traffic from all affected

nodes (H, I, J).

5 Link H-I Node H cannot access the

core.

Node H cannot access the core but the

steerable smart antenna directs its beam

from I to J and establishes a new terrestrial

link. The increased traffic can be offloaded

through the satellite connection at node I.



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A B C

D

E

F

G

H

IJ

Mobile Core Network/EPC


Gateway antenna

Satellite backbone fibre

network


network

Ka band GEO satellite

TeleportTeleport

BEFORE LINK FAILURES

Satellite hub



Figure 2-1: Radio link topology before failures



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SA

A B C

D

E

F

G

H

IJ



Gateway antenna


network


network

Ka band GEO satellite

TeleportTeleport

Link Failures

New Links

Event 1

Event 2

Event 3

Event 4

Event 5

EVENTS AND SOLUTIONSSatellite

hub



Figure 2-2: Radio link failures events and solutions

2.2.2 Radio link congestion One of the SANSA use cases is to provide offloading capability via satellite to the backhaul network.

This use case is illustrated in the Figure 2-3 below.

Figure 2-3a presents the network topology before the events of congestion. Based on the topology

all the nodes are routing their traffic appropriately so that they reach Node G that is connected to

the EPC with optical fibre. The arrows indicate the flow of traffic within the backhaul network.

In Figure 2-3b four congestion events occur in the network:

Event 1: Heavy congestion on the link B-C which affects the traffic coming from Nodes A and

B.

Event 2: Moderate congestion on the link D-G which affects the traffic coming from Nodes A,

B, C and E.

Event 3: Heavy congestion on the link F-G which affects the traffic coming from Nodes I, J

and H.

Event 4: Moderate congestion on the link I-F which affects the traffic coming from Nodes J

and H.



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The congestion events trigger the HNM to adapt the topology to optimise the overall performance.

Figure 2-3c illustrates how the topology changes to tackle the congestion events:

Event 1: Node A activates the satellite link for backhauling instead of forwarding the traffic

to Node B which helps decongest the link B-C.

Event 2: In Node E part of the traffic is offloaded thought the satellite link resulting in a

reduction of the total traffic arriving at Node D. Subsequently the link D-G is decongested.

Event 3: The SA in Node F creates a second link with Node E (F-E) so that the traffic from

Node F is split between the links F-G and F-E. The traffic arriving at Node E is then

backhauled through the satellite link of the node.

Event 4: As the link I-F is starting to become congested, Node I offloads part of the traffic

through the satellite link.

The events description and responses are presented in

Table 2-2.

Table 2-2: Congestions events description and responses

Event Congestion events Response

1 Heavy congestion on the link B-C which

affects the traffic coming from Nodes A and

B.

Node A activates the satellite link for

backhauling instead of forwarding the

traffic to Node B which helps decongest the

link B-C.

2 Moderate congestion on the link D-G which

affects the traffic coming from Nodes A, B, C

and E.

In Node E part of the traffic is offloaded

thought the satellite link resulting in a

reduction of the total traffic arriving at

Node D. Subsequently the link D-G is

decongested.

3 Heavy congestion on the link F-G which

affects the traffic coming from Nodes I, J and

H.

The SA in Node F creates a second link with

Node E (F-E) so that the traffic from Node F

is split between the links F-G and F-E. The

traffic arriving at Node E is then backhauled

through the satellite link of the node.

4 Moderate congestion on the link I-F which

affects the traffic coming from Nodes J and

As the link I-F is starting to become

congested, Node I offloads part of the



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H. traffic through the satellite link.

A B C

D

E

F

G

H

IJ



a) BEFORE CONGESTION

b) CONGESTION EVENTS

A B C

D

E

F

G

H

IJ

Event 1

Event 2

Event 3Event 4



c) CONGESTION RESOLUTION

A B C

D

E

F

G

H

IJ


network


networkMobile Core Network/EPC




New links

Not congested links

Moderately congested links

Heavily congested links



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Figure 2-3: Congestion use case for the rural scenario

2.2.3 New node deployment/incorporation The deployment and incorporation of new nodes is a major issue for mobile operators. One of the

SANSA targeted contributions is to provide operators with hybrid nodes that are low cost, easily

deployable and energy efficient.

The work on cost effective solutions regarding the antennas along with the use of already existing

technology as far as terrestrial equipment is concerned will have a positive impact on the overall

hybrid node cost.

SANSA offers flexibility as a result of the hybrid nature of the nodes that incorporates and reassure

seamless connectivity through satellite or terrestrial paths. In practice this will result in a solution

that is not heavily dependent on the already existing infrastructure as satellite connection ensures a

high capacity solution is available in areas with poor backbone network infrastructure and areas

where is difficult geographically to establish a microwave link. The operators do not have to wait for

new backbone infrastructure to be developed before they can deploy their new nodes.

As far as energy consumption is concerned, new nodes will have minimized power consumption and

the smart network reconfiguration and power mode central management will make sure that there

is no excessive power consumption with positive impact on both OPEX costs and deployment in

areas where power supply is limited (e.g. use of photovoltaic panels to supply with power the hybrid

node).

2.2.4 CDN integration As far as Content Delivery Networks are concerned, within the scenarios, the integration of these

networks can be supported either by a sole satellite connection or through combined satellite and

terrestrial links.

2.2.4.1 Satellite fed cache CDN In this case all the content sent to the edge CDN is fed only through satellite. The content is

delivered to the cache, which is located at the eNB, through the satellite connection as can be seen

in Figure 2-4.



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Figure 2-4: Satellite fed CDN cache

2.2.4.2 Cache fed through satellite and terrestrial link In this case the CDN edge network is fed both through the satellite and the terrestrial connection

available at the eNB. The content is delivered to the cache either through the satellite or through the

terrestrial connection depending on the network conditions as can be seen in Figure 2-5.

Figure 2-5: CDN cache fed through satellite and terrestrial connection



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2.2.5 Remote cell connectivity

2.2.5.1 Standalone cell One of the main problems that current mobile networks encounter is the difficulty in deploying

network infrastructure in areas that are isolated (e.g. islands), or areas that lack backbone

infrastructure and the geographical location does not allow the establishment of microwave links.

Standalone cells can bypass the lack of infrastructure by sending data through a satellite connection.

Figure 2-6: Remote cell connectivity – Standalone cell

2.2.5.2 Moving base station The SANSA system can facilitate the backhauling of remote cell sites. In the moving platform (e.g.,

cruise ship) scenario, we distinguish between two different use-cases.

Use-case #1: Moving platform as a remote cell site

In this use-case, the SANSA system facilitates the backhaul connectivity to a moving platform, as

shown in Figure 2-7.



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Figure 2-7: Moving platform as a remote cell

Use-case #2: Moving platform facilitating remote cell backhauling

A less common use-case is the one wherein the moving platform facilitates the backhauling of a

remote cell site. For example, consider a complex of islands where traffic is backhauled through a

multi-hop chain of terrestrial microwave links. Assume that a cruise ship equipped with an iBN

approaches the coast of one of these islands. In that case, it can provide satellite backhauling to the

corresponding remote cell, as it is shown in Figure 2-8.



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Figure 2-8: Moving platform facilitating the backhauling of a remote cell

2.3 Relation of Event periodicity to the Selected Use-cases The main characteristic of the SASNA network is re-configurability in terms of topology and

connectivity between links as it takes advantage of having the smart antennas along with the

satellite connected backhaul nodes.

The radio link failures as well as the congestion events are occurring the same way and with the

same frequency in both urban and rural deployment. As an example, the urban deployment involves

medium-to-high dense network in the normal working environment, and any additional event

normally add more traffic to the network and may cause network congestion. The events can be

classified into the following categories according to their occurring frequency. Without loss of

generality, the description will be based on the congestion link use case; link failure can be

interrupted similarly.

2.3.1 Periodic-occurring events These events include both the temporal and/or spatial periodicity. In terms of congestion related

with time, mainly the residence areas will have more traffic at night or non-working days, while the

industrial/offices zones and universities usually have high traffic demand during working hours.

Having part of the backhauling nodes with the satellite connection ability will prevent possible



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network congestion. An example of this case is explained in Figure 2-9 where the university

backhauling node A is connected to the Evolved Packet Core (EPC) via terrestrial networks. In case of

low traffic like non-working hours, the backhaul link can support the active nodes with no problem.

As the traffic increases in the working hours, the link to the EPC might be congested –the same in

case of link failure-, the backhauling node has two alternatives; a) to reach the EPC through the

backhauling node C as ACD or b) to get benefit from the satellite backhauling. The decision will

be part of the work to be done in other WPs depending on the type of the traffic, the load on the

node C, etc.

Figure 2-9: Periodic occurring events

2.3.2 Semi-periodic events

These types of events consider the case where high peak of traffic is generated due to regular

celebration, meeting or occasions. One expressive example is the sport stadium where the local

team plays home matches. In such a case, the stadium coverage would benefit from having one or

several hybrid backhauling nodes that are able to tackle the increment in the traffic and over some

additional bandwidth temporal need as depicted in Figure 2-10.



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Figure 2-10: Semi-periodic occurring events

2.3.3 Rarely repeated events This category of events counts for the meetings or festivals with no prior special network node

planning. These types of events differ from the previous ones in that it’s possible that there is no

hybrid backhauling nodes placed in the event site like the stadium or the university examples. In this

case the network should react rapidly where the nearest hybrid backhauling node can off-load the

generated traffic. Example of this type of events is depicted in Figure 2-11 where the link CD is

congested due to the high traffic demand and the alternative CA link is used where the node A is

the nearest hybrid backhauling node.



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Figure 2-11: Rarely repeated events

2.3.4 Seasonality Another aspect of the periodicity of the events is their seasonality. Summer and winter holiday

destinations face traffic fluctuations throughout the year that depend on the season. Summer

resorts are encountering high traffic demands during summer months whereas winter destinations,

like ski resorts are having the same problem during winter months.

SANSA through a mechanism similar to the one presented in 2.3.1 Periodic-occurring events will

offload traffic during peak months.



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3. SANSA Scenario Definition

3.1 Overall strategy

There is a five axis presentation of the various elements that could jointly provide a well-defined

scenario as illustrated in Figure 3-1.

Figure 3-1: SANSA scenarios characterization



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The Ka-Band shared spectrum between terrestrial and satellite links. This could be the downlink or

both uplink and downlink. The main case in the scenario definition is the DL only spectrum. This is

because there is no need to extend bandwidth in the UL direction, due to FWD:RTN ratio increasing

(i.e. in excess of 6:1). Shared spectrum in the uplink also requires a change in regulations. The

scenarios, where interference in both uplink and downlink exists, are provided mainly for research

and interference mitigation techniques enhancement reasons and may be used in the future in case

of highly increased traffic demands to support the deployment of satellite terminals in the 27.8285 –

28.4445 GHz and in the 28.9485 – 29.4525 GHZ bands.

The satellite carrier bandwidth is also a very important factor regarding the scenario definition

process. The main three carrier types that will be examined through SANSA are the state of the art

(SOTA) carriers (54 MHz downlink and 9 MHz uplink carrier bandwidth). Since SANSA is an R&D

project aiming at providing backhaul solutions within the 2020 timeframe, the beyond state off the

art concerning carrier bandwidth should be taken into account. The other two references regarding

carrier are BATS, with a carrier bandwidth size of 421 MHz for the downlink and 21.7 MHz for the

uplink [64] and UWB with a carrier size of 230 MHz for the downlink and 9 MHz for the uplink 0.

Another important distinction between several scenarios is the type of deployment. Urban

scenarios are the scenarios with high node density, including small cells, high traffic requirements

but easy access to high speed optical fibre networks as well. On the other hand, rural scenarios are

for less populated areas with microwave link connections mainly and not easy access to fixed high

speed broadband networks. Another type of deployment is mobile platform deployment for trains,

ships, airplanes etc.

The CDN design is an emerging need for modern mobile networks as this type of traffic has an

increasing trend and will be the dominant type of traffic within the years to follow as already

mentioned in the state of art deliverable [2]. The existence of a CDN could be examined here as well

as how CDN cache should be fed, either through a terrestrial or a satellite link. We should also be

able to prepare nodes to facilitate the installation of such caching systems in case this will be

required in the future.

The last important factor in the scenario definition process is the type of the terrestrial links.

Antenna characteristics, channel characteristics, carrier characteristics and every link characteristic

should be clearly defined for each selected scenario.

In the next figure (Figure 3-2) there is a compact representation of the scenario selection strategy. A

matrix that takes into consideration all the above mentioned elements that can lead to a well-

defined scenario and places them in it.



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Figure 3-2: Scenario selection strategy matrix example

3.2 Strategy for designing and implementing a terrestrial backhaul system

The strategy that is followed for the design, configuration and implementation of a terrestrial

backhaul link usually follows specific steps for designing the links; For the design, the implementer

considers: the broadband rate that needs to be supported, the resilience of the link so that the

connection between the nodes is not lost, flexibility in terms of resource handling and service

provisioning and compatibility between old and new installed equipment.

Topology examples (PtP, PtMP, backhaul of small cells)

The PtP and PtMP topologies have been provided in D2.1. In addition there are topologies which are

followed from small cells which are considered to be very interesting from the point of view of 5G

technologies.

Small cell deployment follows the Mobile Broadband (MBB) network densification for confronting

the data capacity crunch in the hot-spot areas. The small cell backhaul (and fronthaul) ecosystem is

an emerging technological area consisting by a large portfolio of interconnection media, including of

course wireless technology.



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A typical use case is small cell network, which is deployed inside the urban street canyon, to be

connected to a nearby macro-cell site and from there entire traffic to be routed back to the core

network by utilizing the same transport infrastructure. In such an implementation the capacity

requirements of the macro-cell backhaul solution shall further increase.

3.3 SANSA selected scenarios Among the numerous scenarios, 6 scenarios in total, 2 for rural, 3 for urban and a moving base

station scenario have been selected to demonstrate the novelties and improvements SANSA

introduces to backhauling technologies with the use of satellite terrestrial hybrid networks as well as

with the use of new components. In Table 3-1 you can find a summarized presentation of the

selected scenarios according to the scenario selection strategy presented in the previous paragraph.

Table 3-1: Selected scenarios on the scenario selection strategy matrix

Spectrum

sharing

Satellite Carrier

Bandwidth

Content Delivery Networks Type of deployment Terrestrial

links

Scenario

ID

DL

only

UL

+

DL

SoTa NG

HTS

UWB No

CDN

Sat-only

Multicast

Sat +

Terr

Multicast

Rural Urban Moving

base

station

18

GHz

28

GHz

Rural 1 + + + +

Rural 2 + + + + + + +

Urban 1 + + + + + +

Urban 2 + + + + + +

Urban 3 + + + + +

Moving

base

station

+ + + + +



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3.3.1 Rural case Rural areas all over Europe lack adequate broadband infrastructure. Fixed lines are usually slow and

mobile communications cannot provide the required speeds to support, hence improvements to

broadband connectivity are needed. The digital divide is present in mobile communications and the

forecast future trends show an increase in traffic demands in these areas too, making it very difficult

to cover future needs as they are forecasted by various reports [17]. The EC’s will to bridge that gap

and allow further growth and development in rural areas is supported by SANSA project and the

corresponding rural SANSA scenarios are built towards this direction.

Resilience, high speed satellite connections for traffic off loading and CDNs that can bring delivery of

specific interest closer to the user are some of the rural scenarios characteristics. The objective of

these scenarios is to further support backhauling networks, bringing as a result faster and more

reliable mobile networks. To achieve these goals will need extensive use of satellite connections as

well as use of innovative key enabling components such as smart antennas, intelligent backhaul

nodes and a hybrid network manager. Moreover, an extensive research on the interference

landscape and spectrum sharing is performed in order to help the designed system maximize

spectrum use.

3.3.1.1 Rural Scenario #1 This is the baseline to be examined throughout SANSA project. Instantiations of this could be used as

relevant rural scenarios for WPs to follow. The basic underlying idea of this scenario is the

coexistence in the same band in the downlink, the use of Next Generation HTS as a carrier

bandwidth reference, CDN cache fed by satellite multicast and terrestrial links at 18 GHz.

Table 3-2: Rural scenario #1 on scenario selection strategy matrix

Spectrum

sharing

Satellite Carrier

Bandwidth


links

Scenario

ID

DL

only

UL

+

DL

SoTa NG

HTS

UWB No

CDN

Sat-only

Multicast

Sat +

Terr

Multicast

Rural Urban Moving

base

station

18

GHz

28

GHz

Rural 1 + + + + +

3.3.1.2 Rural Scenario #2 R&D scenario UL & DL spectrum sharing should be taken into account. Interference mitigation

techniques to support the coexistence of terrestrial and satellite links for both uplink and downlink



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are needed. This is a useful scenario for future reference in case all allocated resources are used (not

in the near future) since channels of some tens of MHz have to use a band of 2 GHz. Any

interference problems in the present or in the near future would be a result of bad network planning

and resource allocation.

Table 3-3: Rural scenario #2 on scenario selection strategy matrix

Spectrum

sharing

Satellite Carrier

Bandwidth


links

Scenario

ID

DL

only

UL

+

DL

SoTa NG

HTS

UWB No

CDN

Sat-only

Multicast

Sat +

Terr

Multicast

Rural Urban Moving

base

station

18

GHz

28

GHz

Rural 2

(R&D) + + + + + + +

3.3.2 Urban Case In the urban scenario, connectivity is required at any place and at any time by humans in dense

urban environments, considering both the traffic between UEs and the Internet and direct

information exchanged between UEs. In terms of services run by the users we can find, besides

classical services such as web browsing, file download, email, social networks, there will be a strong

increase in high definition video streaming and video sharing. The particular challenge lies in the fact

that users expect the same quality of experience at their workplace, when enjoying leisure activities

such as shopping, or while moving on foot or in a vehicle. Furthermore, a particular aspect arising in

urban environments is that users tend to gather and move in “dynamic crowds”. A moderate

increase in terms of traffic demands can be considered cases like people waiting at a traffic light, or

at a bus stop. An intensive increase of traffic demands can be considered the case of a stadium

where thousands of people gather to watch a sport event.

To tackle these use cases in the urban scenario, network densification is important because of high

traffic volumes and their unpredictable traffic demand fluctuations. With large and unexpected

traffic demand fluctuations, the only solution in tree and ring topologies is to add higher capacity

links. In turn, as the increase of traffic demands can happen anywhere in the network, all the links in

the network would potentially require the addition of higher capacity links. On the other hand,

meshed solutions allow traffic to be load balanced over the topology to mitigate congestion, or using

alternative paths in case of link failure. A subset of all the backhaul nodes comprising the urban

scenario will include satellite backhaul link to reach the EPC. All backhaul nodes will include



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terrestrial links to reach the EPC. The UEs will share the backhaul links for backhauling. The SANSA

system will bridge the gap for the coexistence of terrestrial and satellite backhaul technologies,

reducing the costs derived from running these two independent wireless backhaul solutions.

For next WPs, we defined three different urban scenarios having in mind the current architecture

and the expected future ones. It is worth mentioning that in order to reflect the impact of the SANSA

it’s always recommended to compare the proposed scenarios with a reference scenario that

contains only fixed terrestrial antennas and with no satellites. Additionally, for all the considered

urban scenarios, medium-to-high density of base stations is assumed with small cell deployments

(e.g., mesh-like deployments). The scenarios are classified based on the timeline of the deployment.

The description of these scenarios is tackled in the next subsections.

3.3.2.1 Urban Scenario #1 This is the basic urban scenario that can be referred to as short-term urban one. In this scenario, the

spectrum is shared in the downlink transmission only where the actual SoTa is used as a reference

for the satellite carrier bandwidth. This scenario considers the terrestrial link at both 18 and 28 GHZ

with no CDN. With this, interference mitigation techniques will only take place at the terrestrial -

satellite downlink transmission.

Table 3-4: Urban scenario #1 on scenario selection strategy matrix

Spectrum

sharing

Satellite Carrier

Bandwidth


links

Scenario

ID

DL

only

UL

+

DL

SoTa NG

HTS

UWB No

CDN

Sat-only

Multicast

Sat +

Terr

Multicast

Rural Urban Moving

base

station

18

GHz

28

GHz

Urban 1 + + + + + +

3.3.2.2 Urban Scenario #2 This scenario reflects the medium-term deployment and is different from the previous one in both

the satellite carrier bandwidth and the level of the content delivery in the network. Having the same

spectrum sharing in the downlink only, this scenario differs in the sense that it uses the next

generation HTS as satellite carrier bandwidth reference. Satellite multicast is the proposed

technique for content delivery. The satellite user data demands for this scenario are higher than in

the previous one, as CDN will be deployed. Since the frequency band granularity of the satellite



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standard will be increased, the frequency allocation capabilities for the hybrid systems will be

increased.


Spectrum

sharing

Satellite Carrier

Bandwidth

Content Delivery

Networks

Type of deployment Terrestrial

links

Scenario ID DL only UL

+

DL

SoTa NG

HTS

UW

B

No

CDN

Sat-

only

Multic

ast

Sat +

Terr

Multic

ast

Rur

al

Urba

n

Movin

g base

statio

n

18

GH

z

28

GHz

Urban 2 + + + + + +

3.3.2.3 Urban Scenario #3 This scenario will additionally consider the UL and DL spectrum sharing and therefore, use of

interference mitigation techniques will be mandatory. Moreover, as CDN in the terrestrial segment is

considered, multicast or multi-group multicast techniques shall be deployed.


Spectrum

sharing

Satellite Carrier

Bandwidth

Content Delivery

Networks


links

Scenario ID DL only UL

+

DL

SoTa NG

HTS

UW

B

No

CDN

Sat-

only

Multic

ast

Sat +

Terr

Multic

ast

Rur

al

Urba

n

Movin

g base

statio

n

18

GH

z

28

GHz

Urban 3 + + + + + +

3.3.3 Moving base station scenario Typically, in cruise ships one or more base stations / access points are installed to provide radio

access to the passengers. Traffic is backhauled with the help of a satellite link. Such a setup can

benefit from the capabilities of the SANSA architecture.

In this scenario, we consider a cruise ship equipped with an iBN, according to the SANSA concept, so

that both a terrestrial and a satellite link are available for mobile backhauling.



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As it is shown in the following table, we assume spectrum sharing only in the DL and utilization of

the SoTA satellite carrier bandwidth.

Table 3-7: Moving base station scenario on scenario selection strategy matrix

Spectrum

sharing

Satellite Carrier

Bandwidth

Content Delivery

Networks


links

Scenario ID DL

only

UL

+

DL

SoTA NG

HTS

UW

B

No

CDN

Sat-

only

Multic

ast

Sat +

Terr

Multic

ast

Rur

al

Urba

n

Movin

g base

statio

n

18

GH

z

28

GHz

Moving base

station + + + + +

The scenario is divided in two sub-scenarios, and each one of them is mapped to two use cases.

Cruise Ship Sub-Scenario #1: Anchored Ship

This scenario refers to an anchored ship. In this case, we can take advantage of the terrestrial

backhauling infrastructure. We distinguish between two use cases:

Use case #1: Only the terrestrial backhauling link is used, while the satellite link serves as

backup solution in case of a terrestrial link’s failure.

Use case #2: Both the terrestrial and the satellite backhauling links are used at the same

time, where the latter link is utilised for offloading the former link and enhancing the

backhauling capacity of the system.

Cruise Ship Sub-Scenario #2: Ship

This scenario refers to a ship. When the ship starts sailing, then the iBN should switch to the

satellite-only mode fast enough, such that no service disruption is encountered. Once the ship starts

its cruise, we distinguish between two use cases:

Use case #1: This use case refers to a cruise ship that is mostly located close to the shore. If

the ship is moving along the coastal line, then from time to time both backhauling options

will be available (e.g., when passing near an island). Hence, the iBN should (a) switch from



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the satellite-only mode to terrestrial-satellite mode or vice versa when the ship approaches

or leaving the shore, respectively; and (b) should make the optimum use of the backhauling

resources when both satellite and terrestrial backhauling options are available (e.g., use

both backhauling links to enhance capacity or use only the terrestrial link if the quality of the

satellite link is not sufficiently high).

Use case #2: This use case refers to a cruise ship that is mostly out in the open sea. While

the ship is at the middle of the ocean, then backhauling will be constantly provided through

the satellite link. When, on the other hand, the ship approaches the shore, then again both

backhauling options will become available as in use-case #1 of this scenario.

These use cases are illustrated in Figure 3-3.

Figure 3-3: Moving base station scenario

3.4 Scenarios General Characteristics

3.4.1 Frequency bands In the context of SANSA, D2.1 [1] studied the regulatory situation of the Ka-band in Europe in order

to assess the feasibility of deploying terminals for High Density (HD) applications in the Fixed

Satellite Service (FSS) accessing the full shared and exclusive civil Ka-band for backhauling traffic

from the cellular mobile networks.

Figure 3-4 illustrates the maximum bandwidth that could be available for the SANSA satellite

segment considering that HDFSS could be deployed in both exclusive and shared parts of the

spectrum.



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Figure 3-4: Maximum available bandwidth for uncoordinated FSS stations based on CEPT implementations [1]

3.4.2 Spectrum sharing between different MNO Currently in the access mobile systems there are several schemes which are used for the spectrum

sharing. These can be summarized as:

License spectrum access (LSA): This is the mechanism where license spectrum is used among more

than one operator. The idea is to utilize unused spectrum of one operator by another MNO in case

that the main operator is underutilizing the spectrum. As an example, if one operator is using a

Frequency Division Duplex (FDD) system where the UL spectrum is underutilized, then it can be

borrowed by small cells to DL Time Division Duplex (TDD) traffic.

License assisted access (LAA): This is a mechanism invented by Ericsson and now 3GPP tries to

standardize it where LTE is used in unlicensed Wi-Fi bands in order to harmonically transfer traffic

from LTE into Wi-Fi technology.

Currently there is spectrum sharing at the access networks in some European countries in

Scandinavia. The backhaul networks usually are independent between different MNOs and no

sharing occurs between their networks mostly because of the competition that does not let easily

the operators to interoperate their networks. However, for the case where satellite and mobile

operators have to share their common spectrum in order to offer better services is very feasible and

advantageous to happen.



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3.4.3 Standards

3.4.3.1 Terrestrial air interface Standards

The standards which are utilized for the PtP links are described mostly in the family of standards ETSI

EN 302 217, while the ones that refer to the PtMP links are described in the family EN 302 326-2.

These links have been very important to be used in the frequency bands from 28-29 GHz since their

use can alleviate constraints such as LOS conditions, capacity performance and also low cost of

ownership (TCO). The spectrum efficiency (bits per Hz) and the spectrum licensing fees in mmWave

backhauling are much lower than the ones used at macro frequencies. Currently most of the

backhaul systems are using FDD technologies and PtP modelling in order to be more robust to

frequency interference; however systems using TDD modelling are increasing. These are more

spectrum efficient and this trend will be accelerated in the future as capacity demands are

increasing. PtMP is used usually in urban areas where traffic demands are high.

Antennas

As the technology of the access network is moving into the arena of 5G, it is seen that large scale

antenna systems are used more often [67]. The LSAS scheme is the one where the base stations

have a large number of antennas attached to them and have been considered to provide system

energy efficiency and spectrum efficiency in future networks. Antenna arrays, where each antenna is

small (mm), and are directional at both TX and RX is an important consideration for the next 5G

MNs.

In addition, if beamforming is used then the number of transceivers can be reduced. This can lead to

lower TCO for the operator, which in turn is an additional factor that is considered for limiting the

power consumption and interference.

PHY interface

Time division duplexing (TDD) is a duplexing scheme that needs to be considered since it allocates

the bandwidth dynamically in time and uses lower cost radio equipment due to the no requirement

on filters.

3.4.3.2 Satellite air interface Satellite air interface standards have been presented in D2.2 [2] as part of the SoTA review of mobile

backhauling enabled by satellites. The main standards that have been studied are DVB-S, DVB-S2 and

DVB-S2X for the forward channel and DVB-RCS and DVB-RCS2 for the return channel.



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Based on the state of the art hardware review for satellite backhaul presented in D2.2 [2], almost all

remote satellite routers receive DVB-S2 signals from the satellite gateway to the VSAT but utilize

proprietary air interfaces for the return link. In the context of SANSA the forward channel air

interface with the satellite will use DVB-S2 based on its widespread adoption but considering its

evolution, DVB-S2X which provides additional MODCODs, smaller roll-off factors and higher

modulation schemes. For the RTN channel we will adopt DVB-RCS2 to maintain compatibility with

ETSI standards.

3.4.4 Regulation In deliverable D2.1 [1] the different types of Licensing Procedures were presented; these are

presented here for completeness:

1. Individual licensing per link: This is the conventional link-by-link coordination, usually made

under administration’s responsibility. This is currently assumed to be the most efficient

method of spectrum usage for point-to-point links. Traditionally, backhaul links have been

registered on a “per link” license. Per link licensing has represented up to 65.5% of license

models in operation. Due to their directive antennas and narrow beam widths, per link

licensing is very common in PtP deployments, particularly in bands from 18 GHz to 42 GHz.

2. Block Spectrum: This is a common method for licensing point-to-multi point networks. The

user of the license is usually free to use the block at best to deploy its network. In some

cases, there might even be no limitation to the wireless communications methods used in

the block (e.g. PtP and/or PtMP, terrestrial and/or satellite, etc.). The assignment of the

block can be made through licensing (renewable, but not permanent) or through public

auction (permanent). Block spectrum assignment has been gaining traction for frequencies

from 28 GHz and above representing up to 20.7% of license models in operation. Per block

licenses are increasingly being used for PtMP links.

3. Lightly licensed spectrum: “A light licensing regime is a combination of license-exempt use

and protection of users of spectrum. This model has a first-come first-served feature where

the user notifies the regulator with the position and characteristics of the stations. The

database of installed stations containing appropriate technical parameters is publicly

available and should thus be consulted before installing new stations. A mechanism remains

necessary to enable a new entrant to challenge whether a station already recorded is really

used or not. New entrants should be able to find an agreement with existing users in case

interference criteria are exceeded”.

4. Shared License: This method is similar to lightly licensing, with a primary and secondary user

of the spectrum in a particular band, location and time.



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5. Unlicensed spectrum: This method provides the most flexible and cheap usage but does not

guaranty any protection to interference.

In the SANSA context we will look both at the individual license per link and block spectrum

assignment as they are the most prevalent types of licensing nowadays. WP3 will explore the

interference mitigation techniques that can be employed for the different interference landscapes

formed by the two types of licensing.

3.5 Nodes distribution and generated traffic

3.5.1 Satellite user terminals deployment A great challenge regarding SANSA network is the deployment of satellite terminals within the

SANSA network. A deployment decision is usually based on a series of factors; these usually are

technological / performance factors, cost and regulatory or special problems that do not allow the

deployment of satellite terminals at a backhaul node. These factors are scenario based and the

deployment would not be the same in a rural, in an urban and in a moving base station scenario.

Ideally every node should have a satellite terminal, but this is not the most cost effective solution. In

a general sense the network should be a compromise between the ideal technical solutions, the

most cost effective solution and should always take into consideration factors that are not directly

related to technological or cost constraints (e.g. regulatory environment).

When it comes to the SANSA reference topologies design, it is very important to make a clear

distinction between the scenarios. It is very important to note that we consider after the regulatory

study conducted in D2.1 [1] that we can design a network that has no other restrictions apart from

technological and cost limitations. For the rural topologies, the main issues as we have already

discussed them in the use case definition are resilience, off-loading, CDN integration and standalone

cells. This means that satellite terminals will have to be placed at nodes where:

The backhaul node is the centre of a star network topology, so that the satellite link will help

with offloading and resilience where the star node is directly connected to the core network.

There is no different way to connect to the core network; this is the case of standalone cells.

Satellite terminals where Edge CDN caches are going to be placed. This will have to be

designed and implemented with the help of the CDN operator.

Every node that in case of link failure will lead to an access network problem, this can

happen to nodes that cannot establish a different terrestrial link with the use of the

steerable beam of a smart antenna.

In the case of urban deployments, the usual case is that nodes are connected to the core through a

superfast connection (fibre optic). This means that satellite links will be mainly used to support CDNs



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and offloading (especially for special events like concerts, football matches etc.). They can also

provide connectivity to urban areas where fibre networks have not been deployed yet and are not

expected to be deployed in the short term.

In the case of the moving base station scenario, satellite terminals will be needed in every node as

those platforms are expected to spend long periods of time having no access to terrestrial networks.

3.5.2 Macrocell deployments This section provides a traffic analysis modelling for current 4G/LTE networks and also a projected

analysis for 5G networks by assuming that heterogeneous networks will be used especially small

cells that are capable of generating a large amount of traffic. The analysis is performed for both

urban and rural cases although the first one is by far the most interesting and the one that generates

most traffic and revenue for the operator.

3.5.2.1 Urban scenario We can make an analysis of traffic by utilizing the characteristic physical parameters provided in the

document 36.214 [68]. Tables in section 7.1 propose basic data rates for current LTE systems and

also for the projected 5G systems. As it is seen in Figure 3-5 and Figure 3-6 we have considered

urban and rural scenario for base stations having 10 MHz bandwidth and two level backhaul

aggregation for the urban case while one level for the rural case. For current systems we can assume

that there are 3 cells per base station (BS) and one macrocell backhaul BS (MBBS) per 3 cells.

Table 3-8: Urban users’ traffic profile

Users/km2 Peak traffic/user Cell radius Cells/BS

4000 10Mbps 2km 3



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Figure 3-5: Traffic analysis for urban scenario

3.5.2.2 Rural scenario The same parameters as above also apply here, but each base station has one cell.

Table 3-9: Rural users’ traffic profile

Users/km2 Peak traffic/user Cell radius Cells/BS

50 3 Mbps 5 km 1



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Figure 3-6: Traffic analysis for rural scenario

3.5.2.3 Projected scenario for a 5G network In Table 3-10 there is a 5G network profile projected traffic by Nokia networks [66] and in Figure 3-7

there is a 5G network consisting of a number of small cells.

Table 3-10: Projected scenario for a 5G network (networks.nokia.com)

Users/km2 Peak traffic/user Small Cell radius Cell edge traffic

4000 1 Gbps 150 m 100 Mbps

Figure 3-7: 5G network consisting of a number of small cells



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3.5.3 Satellite and terrestrial content delivery traffic profile In order to study this problem, a traffic model based on the multimedia popularity is defined in this

section. The popularity is measured based on the number of requests and can be described though a

probability function. A widely-used abstraction for this function is the Zipf law, which is given by [3]:

In more detail, if we ordered the files from most to least popular at a given point in time, then the

relationship governing the frequency at which the file of rank i will appear, is given by the equation

presented above. Consequently, the probability of a request occurring for file i is inversely

proportional to its rank, with a shaping parameter α. A detailed analysis on how to choose the exact

value of α is described in [4]. The following figure (Figure 3-8) provides an example of the Zipf law:

Figure 3-8: Zipf law

3.6 Interference landscape In this section we consider all the possible sources of interference at the backhaul node level and

assess whether they are relevant to the SANSA solution. It is important to note that in the context of

the project we refer to co-channel interference i.e. the interference caused by two or more

transmitters using the same frequency.



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Considering the SANSA network as a system we distinguish interference in intra- and inter-system

interference. Intra-system interference is caused by transmitters that belong to the SANSA system,

whereas inter-system interference is caused to the SANSA nodes from external transmitters using

the same frequencies. The possible sources of interference are illustrated in Figure 3-9.

3.6.1 Intra-system interference The intra-system interference can be either between the satellite and terrestrial links or only

between the terrestrial links.

3.6.1.1 Interference between satellite and terrestrial links Based on the spectrum sharing schemes between the satellite and terrestrial links that have been

identified for the different scenarios in Table 3-1, the possible causes of interference are:

From eNodeB (eNB) to neighbouring satellite terminal (DL): This is the main case of interference relevant to all the defined scenarios where spectrum sharing is implemented between the satellite DL and the terrestrial links. WP3 will examine techniques to protect the satellite terminal from the interference of an adjacent eNB operating at the same frequency.

From eNB to neighboring satellite terminal (UL): This case of interference is valid if there is shared spectrum between the satellite uplink and the terrestrial links which is not possible under the current regulatory environment.

From satellite terminal to neighbouring eNodeB (UL): This case of interference is valid if there is shared spectrum between the satellite uplink and the terrestrial links which is not possible under the current regulatory environment. There are only two long term scenarios (Rural 2 and Urban 3) that are using this case of spectrum sharing and are scenarios that are not supported by the current regulatory environment but will the coexistence and deployment of terrestrial and satellite links in Ka band and specifically in 27.8285 GHz – 28.4445 GHz and 28.9485 GHz – 29.4525 GHz.

From satellite terminal to neighbouring eNB (DL): In this case there is no interference from the satellite terminal to the eNB as the satellite terminal is only receiving at the shared frequency and not transmitting.



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Figure 3-9: Interference landscape in the SANSA system

3.6.1.2 Terrestrial to terrestrial link Apart from the interference mitigation techniques that enable spectrum sharing between the

satellite and terrestrial links, it is important to investigate solutions for interference between

terrestrial links in the SANSA network. The main technique used for this will be appropriate

frequency reuse schemes depending on available spectrum resources.

3.6.2 Intersystem interference Inter-system interference can be caused by terrestrial and/or satellite links operating at the same

frequencies from different operators. WP3 plans to briefly study this scenario for the case of block

spectrum assignment and per link license.

3.7 Benchmarking topologies

3.7.1 Rural topologies In this report, we choose a typical topology from the Finnish 28 GHz database obtained by the

University of Luxembourg. Note that we don’t have any claim regarding if the chosen topology

represents a backhaul network necessarily, however it provides a good example to perform some

interference and availability analysis. As shall be shown later, such an analysis provides a good

benchmark for the underlying requirements in SANSA reference system.

In the next subsection, first we present the chosen topology located in Helsinki. Note that even

though Helsinki is a big city, in general it consists of small height buildings. Moreover, the suburban



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area of Helsinki examined here presents quite sparse building population which is a typical

characteristic of a rural environment.

3.7.1.1 Topology Example: Helsinki The selected topology is depicted in Figure 3-10. As we can see this topology consists of a number of

interconnected star topologies. This topology based on the actual data in the database is composed

of 28 links and 15 actual locations (nodes). In Table 3-11, we may see the underlying parameters

defining each link as derived from the Finnish database. Further, Table 3-12, presents the location of

each node. It should be noted that all depicted links are bidirectional.

Figure 3-10: Example backhaul topology obtained from the Finnish 28 GHz database, Helsinki.



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Table 3-11: Detailed information of each link



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Table 3-12: The location of nodes

Table 3-13: Connectivity matrix



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3.7.1.2 Benchmark SINR distribution

In this section, we employ the ITU-R 452-16 interference modelling, including the free space loss as

well as the diffraction loss based on the Bullington model to derive the SINR of each receiver based

on the coordinated frequency plan in Table 3-11. This result which will be considered as the

benchmark SINR distribution is presented in Figure 3-11. We can see that all the receivers

experience SINR > 42dB, while a significant number of them experience SINR > 60dB. This is to be

expected since the benchmark topology is the outcome of careful network planning through link

registration by the national regulator.

Figure 3-11: Benchmark SINR distribution of the coordinated frequency plan in Table 3-11

3.7.1.3 SINR and interference analysis: Aggressive Frequency Reuse

In this section, we will move towards the concept of shared access promoted by SANSA, and analyse

the performance of each link, when all employ the same frequency plan. It should be noted that this

is a worst case scenario and less aggressive frequency reuse could be used in practice. We further

would like to estimate the number of required nulls to be produced by each SANSA smart antennas

to tackle the strong interferers. Here, we define the strong interferers based on the ITU-R



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recommendations [5]. An interferer is considered to be harmful if the level of received interference

increases the noise floor by 10%.

Figure 3-12 depicts the SINR distribution of the links when full frequency reuse is employed. We can

note that in this case the lower value of SINR is reduced to around 22dB from 42dB in the

benchmark model. Further, none of the links experience SINR > 48dB. This is explained by the

increased internal interference among the SANSA links. It should be noted that further degradation

might be experienced if inter-system interference from external links is taken into account.

To evaluate the number of strong interferers in each link and thus the required number of nulls in

each SANSA designed smart antenna, we can look at Figure 3-13, where the distribution of the

number of required nulls is presented. Based on this figure, we can deduce that each node needs to

be able to produce 7 nulls in average. It is expected that if less aggressive frequency is used in

combination with carrier allocation optimization, a smaller number of nulls will be required. Thus,

this number can be considered as an upper bound requirement in SANSA smart antenna techniques.



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Figure 3-12: SINR distribution of the links with aggressive frequency reuse



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Figure 3-13: Distribution of the required number of nulls with aggressive frequency reuse

3.7.1.4 Terrestrial to Satellite User Terminal

In this section the impact of employing satellite links for backhauling is studied for the example

topology of Section 3.7.1.1. To that end we replace the terrestrial terminals of nodes 1, 8 and 10 of

the existing topology with satellite ones and study the interference from the remaining terrestrial

nodes. The provided analysis can be considered as a worst case scenario since we assume full

frequency reuse and the satellite terminals are placed on the nodes with the largest number of links.

It is assumed that the satellite terminals on these three nodes are pointing to the HYLAS 2 and 31.7𝑜

East. Based on the node’s position, the satellite antennas should have elevation and azimuth 21.7𝑜

and 176𝑜 respectively in order to point in this satellite group. The satellite link characteristics that

were used are the ones of Section 1.



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Let us study now the interference generated to the satellite terminals by the terrestrial ones. To that

end, in Figure 3-14 we plot the aggregated interference that each one of the satellite terminals is

experiencing. As we can see, for the specific topology and the elevation angles of the satellite

terminals, the interference levels are very low so that there is no need in placing nulls in their

direction. The latter is also verified by Figure 3-15 where we plot the SINR of each one of the satellite

nodes along with the SNR. As it is shown, each node experiences interference that decreases its SINR

less than the 10% of the SNR floor, so based on the ITU-R recommendations the interference can be

considered as non- harmful [5]. Note that in cases where the satellite noses are experiencing

harmful interference from the terrestrial ones, the latter may apply transmit beamforming

techniques in order to null out the interference in the satellite ones.

Figure 3-14: Aggregate Interference on the satellite terminals due to terrestrial transmissions



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Figure 3-15: SINR of the satellite terminals

3.7.1.5 Satellite User Terminal to Terrestrial

Let us now move to the uplink scenario where we are interested for the interference to the

terrestrial terminals generated by the satellite ones. It is assumed that the satellite terminals have

the same azimuth and elevation parameters to the ones of Section 3.7.1.4. The satellite link

characteristics that were used are given in Table 3-14.

In Figure 3-16, we plot the distribution of the number of nulls required per terrestrial link due to the

transmission of the satellite terminals. The calculations are based again on the ITU-R

recommendations [5]. As it is shown, there is requirement for at most one null in only 9 links. The

latter result is very promising since the required number of nulls can be easily handled by the

antenna infrastructures of the typical backhaul nodes by the application of standard receive

beamforming strategies.



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Table 3-14: Simulation parameters for uplink

Figure 3-16: Distribution of the number of nulls per link during uplink



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3.7.2 Urban topologies: The Vienna case In contrast to the rural case, it is expected that in urban scenarios a denser link deployment is

performed due to the extremely high forecasted traffic increase. As a result, a high number of

interfering will be present at each receiver. In addition, as a consequence of the population

densification and its corresponding massive cell (pico, small and macro) deployment, the distances

between nodes will be 1-2 Km maximum, leading to a substantial increase of the interference power

level.

The scope of this section is to provide a scenario example for the urban case. With this definition,

the main interfering cases are described so as an example urban topology.

3.7.2.1 Methodology For the description of the wireless backhaul topology we have used the software iQ-linkXG [6] whose

free version allows to study up to 22 microwave links. This software has available a numerous set of

radio transceivers, antennas and other additional features. After the nodes are deployed within a

map, iQ-linkXG is able to compute the interfering signals, link budgets and terrain profile taking into

account buildings.

This software only has available links at 28 GHz so that, numerical results at 18 GHz can be

extrapolated considering a proportional antenna size in order to compensate the path loss.

Moreover, we will assume full frequency reuse among the links in order to obtain a large bandwidth.

Unfortunately, the satellite link is not straight forward to be included in the software. Consequently,

we evaluate the interference power levels considering an ad-hoc example which will indicate the

major sources of interference.

3.7.2.2 Topology

The topology can be observed in Figure 3-17.



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Figure 3-17: Network Topology for urban deployments

This topology has been obtained considering the city of Vienna. In Figure 3-18, on can be observe

the topology overlaid on Google Earth data.



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Figure 3-18: Network Topology over Google Earth picture.

The deployment has been done considering the specific characteristics of this city and the future

deployment of small cells.

First, Vienna has a tower in the city surroundings that could be equipped with several microwave

links (Figure 3-19). We will consider that this tower has direct connection with the EPC.

Figure 3-19: Tower details

Since Vienna city has a football stadium, we consider that it will be equipped with two small cells

whose backhaul is connected through the microwave wireless backhaul (Figure 3-20).



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Figure 3-20: Stadium details

Finally, different nodes have been considered depending on the area population (city centre,

business centre).

3.7.2.3 Interference analysis

Using the interference analysis tool in iQ-link, we identify the major sources of interference. These

examples are described in the following subsections.

3.7.2.3.1 Methodology

For quantizing the interference power levels we have considered that all links (both terrestrial and

satellite) operate at the same frequency band, in the 28 GHz. As discussed previously, the results are

valid for both the 18 GHz and 28 GHz one as the antenna and power can be scaled accordingly in

order to meet the SNR requirements.

For the sake of simplicity we have assumed the same antenna pattern for both links (terrestrial and

satellite). This is described in Figure 3-21.



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Figure 3-21: Antenna discrimination angle

Remarkably, the discrimination is the same for both the elevation and azimuth angles.

For the 28 GHz case, we considered the Alcatel-Lucent 9400 AWY model [7]. The EIRP for the

terrestrial node is assumed to be 50 dBm (in 30 MHz). Moreover, we consider that all

communications take place in the same frequency bin. For the evaluation of the interference in the

18 GHz band, we have considered ETHEFLEX transceiver [8] operating with a bandwidth of 30 MHz

and a target bit rate of 138.7 Mbps. This leads to a required SNR of 27 dBs.

3.7.2.3.2 Case 1: Co-located microwave links

This case considers the interference received in the link node11-tower from other transmitters

located at the tower. Figure 3-22 summarizes the interference power levels received at the

transceiver detecting the signals from node11.



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Figure 3-22: Interference analysis Case 1

It can be observed in the previous plot that the resulting C/I are dramatically low. This case shall be

considered by WP3 in order to provide a solution for nodes receiving and transmitting information in

the same band. As a first approach, the different links could be allocated in separate frequency bins.

3.7.2.3.3 Case 2: Terrestrial Links

This case considers the interference received from terrestrial links located at different nodes. The

following plot depicts the histogram of the SINR values of the described topology (Figure 3-23).

Figure 3-23: Interference analysis Case 2

The values centred in -40 dB range correspond to the co-located links described in the previous

subsection. The ones that appear in the right on the diagram correspond to general links which

suffer from certain interference power levels. Indeed, even though certain links operate in a very

high SNR, there are others whose SINR is close to 0 dBs.

-60 -40 -20 0 20 40 600

1

2

3

4

5

6

7

8

9

SINR [dBs]

Lin

ks



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Consequently, the interference mitigation techniques are mandatory in order to achieve high SINR

values so that the future traffic demands are properly supported.

3.7.2.3.4 Case 3: Satellite user terminal to terrestrial node This case assumes spectrum sharing in the 28 GHz band for a satellite user terminal and a terrestrial

node. The aim of this analysis is where the terrestrial node receiver shall perform any kind of

interference mitigation.

Table 3-15: Interference data for Case 3 interference analysis

Satellite return link values Terrestrial link values

Frequency 28 GHz Frequency 28 GHz

EIRP 76 dBm EIRP 53 dBm

Bandwidth 1.28 MHz Bandwidth 30 MHz

FSL in 1Km 117.5 dB FSL in 1 Km 117.5 dB

RSL at the terrestrial

node receiver

26.5 dBm RSL at the terrestrial

node receiver

-30.5 dBm

Sensitivity 64 QAM at

10E-6 BER

-74 dBm

Minimum SINR for 64

QAM

27 dB

As presented in the Table 3-15, we will assume an example of a 1 Km terrestrial link. The satellite

values are obtained from Avanti input in Section 2. Bearing in mind that the link requires to operate

at 138.7 Mbps, the minimum SINR is 27 dB. Considering this operative point, the maximum received

interference can be -62 dBm. It has been considered that both the satellite user terminal and the

terrestrial node are located in 1Km distance (see Figure 3-24).

For achieving the maximum value of interference power level, the antenna discrimination of both

the terrestrial receiver and the satellite user terminal shall be of 88.5 dB. This value indicates that

interference mitigation techniques are mandatory for this interference scenario.



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Figure 3-24: Case 3 interference at 28 GHz

3.7.2.3.5 Case 4: Terrestrial node to satellite

This section considers the case of interference from terrestrial node towards the satellite received

signal at the 28 GHz band. The following table describes the considered values.

Table 3-16: Interference data for case 4 interference analysis

Satellite return link values Terrestrial link values


EIRP 76 dBm EIRP 13.7 dBm

Bandwidth 1.28 MHz Bandwidth 1.28 MHz

FSL in 37000 Km 212.7 dB FSL in 37000 Km 212.7 dB

RSL at the satellite -136.7 dBm RSL at the satellite -199 dBm

Required C/N for 8PSK

6/7 DVB-RCS BER 10E-

6

10.7 dB

It is important to remark that it is required to recompute the EIRP for the terrestrial link as we are

considering a lower bandwidth (1.24 MHz) dictated by the satellite link. As it can be observed, even

though the terrestrial link points directly to the satellite, the received signal levels are extremely

unbalanced (62.3 dB). Due to that, for the usual case, this interference will not likely occur.



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3.7.2.3.6 Case 5: Terrestrial node to satellite user terminal

This section studies the case where a terrestrial node interferes with the reception of the satellite

signal by a satellite user terminal. The band considered is 18 GHz. The next table (Table 3-17) details

the parameters used.

Table 3-17: Interference data for case 5 interference analysis

Satellite forward link values Terrestrial link values


EIRP 84.33 dBm EIRP 53 dBm

Bandwidth 54 MHz Bandwidth 30 MHz


RSL at the satellite

user terminal

-98.3 dBm RSL at the satellite

user terminal

-64.5 dBm

Required C/N for 8PSK

6/7 DVB-S2 BER 10E-6

6.6 dB



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Considering again that the terrestrial link and the satellite user terminal are located within a distance

of 1 Km. From the above presented table it is evident that interference mitigation techniques are

mandatory considering the different RSL. Indeed, the maximum received interference power level

for operating at 86.9 Mbps is -119.04 dBm. As a result, the terrestrial node shall implement an

interference mitigation technique in order to provide a discrimination angle of 92.5 dB.


3.7.2.3.7 Case 6: Satellite to terrestrial node

This section describes the interference values between the satellite and the terrestrial node. The 18

GHz band is considered. The following table describes the considered parameters.

Table 3-18: Interference data for Case 6 interference analysis

Satellite forward link values Terrestrial link values


EIRP 84.33 dBm EIRP 53 dBm

Bandwidth 54 MHz Bandwidth 30 MHz




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RSL at the terrestrial

node

-98.3 dBm RSL at the terrestrial

node

-64.5 dBm

Required SINR for 64

QAM BER 10E-6

27 dB

As described in Case 3, the maximum interference power level at the terrestrial node is -62 dBm. For

this case, it can be observed from the table that even though the terrestrial link points to the

satellite, the satellite received signal is below the threshold. As a result, this case can be considered

as a secondary in terms of importance for the interference mitigation techniques development.


3.7.3 Moving Base Station Maritime mobile communications present unique challenges regarding the application of mobile

backhauling. In SANA, we envision an advanced system wherein an iBN is installed on the ship to

provide both terrestrial and satellite mobile backhauling capabilities, as it is shown in Figure 3-28.



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Figure 3-28: Cruise ship topology

The differences of this scenario with the urban and rural scenarios are the following:

When the ship is at open sea, there is no interference from neighbouring terrestrial links.

Regardless whether the ship is anchored or sailing, we have to take into account fading

caused by the movement of the ship or / and the reflection of the transmitted signal from

the sea surface.

3.7.3.1 Fading due to Reflection of the Signal from the Sea Surface

The received signal consists of the sum of a direct component and reflected waves. Multipath

reflections from the sea surface are composed of a specular (coherent) component and a diffuse

(incoherent) component. The former component is phase coherent with the direct wave, whereas

the phase of the latter component varies randomly with the motion of the sea waves. The coherent

component is produced by specular reflection from the sea, while the incoherent component is

generated by reflections from multiple statistically independent points on the sea surface. The

magnitude of these components depends on the roughness of the sea surface and the elevation

angle. Their effect is more prominent for low elevation angles. For calm sea surface, the specular

component dominates the radio propagation. This is in contrast with the typical situation in land

mobile channel modelling, where the specular ground reflection is commonly ignored. However, its

impact vanishes rapidly as the roughness of the sea surface increases. The diffuse component is not

affected that much by the roughness of the sea surface; however, in general its magnitude increases

as the roughness of the surface increases.

Having that in mind, we model the received signal as:



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,r t s t g t d t n t

where s t , g t , d t and n t

where , , and are the direct, specular, diffuse and additive Gaussian noise components,

respectively. In complex baseband representation we have:

2

2

2

Re

Re ,

Re

c

c G

c k

j πf t φ

j πf t φ

j πf t φk

k

s t Se

g t Ge

d t D e

where S , G , kD and φ , Gφ and kφ

where , , and , and are the magnitude and phase of the direct, specular and diffused components,

respectively, and cf is the carrier frequency.

These signals can also be expressed in terms of their in-phase and quadrature components as:

cos2 sin2

cos2 sin2

cos2 sin2

cos2 sin2

i c q c

i c q c

i c q c

i c q c

r t r t πf t r t πf t

s t s t πf t s t πf t

g t g t πf t g t πf t

d t d t πf t d t πf t

where the subscripts i and q denote the in-phase and quadrature signals, respectively. When the

number of diffuse components is large, then id and qd and are modelled as Gaussian random

variables, as a consequence of the central limit theorem. Typically, it is assumed that they have zero

mean and common variance dσ .

The in-phase and quadrature components of the received signal can be expressed as:

i i i i

q q q q

r t s t g t d t

r t s t g t d t



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or, equivalently:

cos cos

sin sin

i G i

q G q

r t S φ G φ d t

r t S φ G φ d t

The envelope and the phase of the received signal are:

1 22 2

1tan

i q

i

q

R t r r

rψ t

r

In the special case where 0S G , the probability density function (PDF) of the envelope follows

the Rayleigh distribution:

2

222

d

R

σ

d

Rp R e

σ

In the other extreme case where 0S , it follows a Ricean distribution:

2 2

2202 2

,d

R S

σ

d d

R RSp R e I

σ σ

where 0I

is the modified Bessel function of first kind and zero order. The Ricean factor K depends on the

elevation angle.



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In most cases, the sea surface is considered to be rough enough to allow us to ignore the specular

component. Hence, typically the channel is modelled as a Ricean fading channel.

Unfortunately, there are very few published works on the characterization and measurements of

multipath fading caused due to sea surface reflections. Even worse, these studies consider

frequencies 10 GHz. For example, the methodology presented in [9] and the corresponding results

regarding the fade depth are only valid in the frequency range 0.8 – 8GHz. Similarly, the model and

measurements regarding the fade depth and fade duration for both calm and rough sea surfaces

described in the [10] refer to the frequency band of 1.5GHz.



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4. Definition of end-to-end SANSA Architecture

4.1 Scope This section discusses the system architecture of the SANSA solution. The first subsection provides

an overall description of the end-to-end system architecture including access, transport, and core

network. This architecture aims at covering all the use cases and scenarios defined in previous

chapters. The second subsection details the transport network architecture (TNA), which is the main

focus of the SANSA project. The architecture of two key enabling SANSA components, the intelligent

Backhaul Node and Hybrid Network Manager is also presented here. Lastly, the architecture for the

moving base station scenario is highlighted at the end of the section.

4.2 SANSA End-to-end System Architecture The SANSA end-to-end system architecture encompasses the LTE-based Radio Access Network

(RAN), the transport network (where the research impact resides), and the Evolved Packet Core

(EPC), also referred to as core network.

The SANSA Access Architecture encompasses the mobile user equipment (UEs) and base stations

(BSs), which can be either macrocells (eNodeBs/eNBs) or small cells (Home eNodeBs/HeNBs). It is

important to note that both macrocells and small cells can be embedded in intelligent Backhaul

Nodes (iBNs) and Backhaul nodes (BNs), as shown in Figure 4-1.

Since SANSA focuses on the transport network, all the 3GPP signalling procedures in the EPC (see

Figure 4-1) and the RAN are adopted without modifications. A detailed description explanation of

the main building blocks and interfaces can be found in [11] . In summary, the main Evolved Packet

Core (EPC) building blocks are:

The Packet Data Network Gateway (PDN-GW) is the entity in charge of connecting the UE to

the external network. The P-GW supports the establishment of data bearers with the Serving

Gateway presented below such as the assignment of IP addresses for the UEs.

The Serving Gateway (S-GW) is the entity in charge of forwarding user plane packets

through the EPC. In particular, it receives tunneled packet from the UE and re-tunnels them

to the PDN-GW.

The Mobile Management Entity (MME) is the entity in charge of handling UE connectivity

and mobility. In particular, amongst other functions, the MME keeps track of the location of

the UEs.

The Home Subscriber Server (HSS) is the functional entity storing subscription data for UEs



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(e.g., user profile, access restrictions for roaming etc).

These entities exchange control plane procedures with the (H)eNBs by means of the S1-MME

interface. In particular, the S1-AP [12] (Application Protocol) provides the necessary control message

signalling between the (H)eNBs and the MME with bearer establishment and mobility management

being some of the network functions it performs.

Regarding user plane traffic, they are tunnelled through various functional entities in the EPC by

means of GPRS Tunnelling Protocol User Plane tunnels (GTP-U) [13]. The S1-U interface provides

user plane tunnelling between the (H)eNodeBs and the S-GW. The GTP-U protocol tunnels user data

between (H)eNodeBs and the S-GW, and between the S-GW and the PDN-GW. The goal of the GTP-U

protocol is to encapsulate IP traffic in flow specific tunnels to provide QoS differentiation. The S5

interface provides user plane tunnelling between the S-GW and the PDN-GW.

It is in the Transport Network where SANSA introduces its main research novelties. In the next

section, we describe the main entities optimized and introduced by the SANSA network.

Figure 4-1: SANSA System Architecture



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4.3 SANSA Transport Architecture The SANSA system focuses on evolving the Transport Network Architecture (TNA). The TNA

describes the network in charge of transporting data between the UEs and the EPC. The SANSA TNA

combines both satellite and terrestrial transport architectures. In this sense, the SANSA transport

network architecture is composed by the following key elements.

The iBN extends the internal architecture of traditional BNs by introducing new functional blocks and

interfaces for the proper management of backhaul satellite and terrestrial resources. Amongst other

functions, the iBN will embed routing, traffic classification, and energy management functions. The

iBN will operate on short to medium timescales and is reconfigurable by the HNM. It will encompass

interfaces to other iBNs, and to the EPC either directly (with a radio link) or through other iBNs.

Finally, any iBN may include a direct connection to the EPC through the satellite network. Note that

the mobile network layer information (e.g. traffic flow from a UE) traverses the iBNs encrypted. We

assume that the iBN is a trusted component by the UEs and EPC, which has enough processing

capabilities, can decrypt mobile network layer information (e.g. traffic class information) tunnelled

through the S1 interfaces to conduct certain functions such as traffic classification and routing of

traffic flows.

The Backhaul Node (BN) is a legacy entity embedding the H(eNB) in charge of carrying transport

traffic to the EPC. It neither presents routing, traffic classification, and energy management

functions. A special case of BN is that of the Mobile Base Station (MBS). The MBS is a BN that

includes mobility capabilities (e.g. a BS in a train). It is an optional element in the SANSA scenarios.

The Satellite (SAT) is a component enhanced by SANSA due to its smooth integration in the

reconfigurable terrestrial transport network. The SAT will encompass an interface to the EPC, and an

interface to iBNs. The interface between the iBN and the SAT allows the system to access the

satellite link status and use the data for traffic classification, routing, topology reconfiguration, and

interference management between the satellite and terrestrial links. Information such as satellite

carrier frequency, channel bandwidth, available data rate and link availability is constantly

monitored by the HNM.

The HNM is a new entity introduced by SANSA which includes functionalities to manage not only

satellite but also terrestrial backhaul resources. Based on global network information view based on

its monitoring capabilities, the HNM is in charge of configuring the topology formed between the

iBN nodes and their connection and configuration of the satellite resources. In this context, it can

configure backhaul resources embedded in terrestrial iBNs, MBSs, and satellite resources. It

operates on long and medium timescales.



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4.4 Intelligent Backhaul Node (iBN) Architecture The iBN is the component that implements the SANSA ground (or terrestrial) transport network. The

iBNs, which are distributed throughout the SANSA meshed network, distribute and forward the user

traffic, and perform network decisions on a short (e.g. routing) and medium (e.g. energy efficiency)

time-scale basis. The iBNs integrate the following main components:

(H)eNB: This generally refers to an LTE base station, or a low-power LTE base station (e.g.

small cell). It is connected to the EPC through a backhaul network.

Routing: This function includes the routing algorithm and is in charge of distributing the

traffic among the different terrestrial and satellite modem interfaces.

Traffic Classification: The Traffic Classification function is in charge of determining the

mapping of traffic flows to the hybrid backhaul resources used to transport them.

Energy Efficiency: This function is in charge of controlling access and backhaul energy

consumption, therefore reducing operator’s OPEX while satisfying traffic demands.

Modems: An iBN includes several terrestrial and/or a satellite modem.

Antennas: According to the type of modem terrestrial smart antennas and/or a satellite

antenna provides the air interface of the iBN.

Beamforming network: This element mixes the outputs of the modems before passing it to

the smart antenna.

A representation of the different components in the iBN can be shown in Figure 4-2:

Figure 4-2: Representation of the iBN components



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4.5 Hybrid Network Manager (HNM) Architecture The HNM is the central element of the SANSA network. This manager aggregates all the network

resources and performs long and medium time-scale configuration changes. According to Figure 4-3,

it includes the following main functions:

Configuration management: This function is in charge of reconfiguring the iBNs in the

network. Also, it is used for distribution of network topology to the nodes. Configurable iBN

items are for instance the terrestrial modems and antennas.

Events management: This component monitors the network nodes and determines the

state of SANSA network.

Topology management: This module performs topology calculations to restore the hybrid

network upon node congestion or failure events. As input, it receives new network states,

and produces new topologies, forwarding them to the configuration management function.

The HNM external components are:

Radio Environment Map: This component calculates interference levels and performs the

carrier allocation. It generates the data that can be later used by the topology management

to calculate effective network throughput.

Satellite Ground Segment: This component is composed by different tools for managing the

satellite network, such as the NMS, the satellite Hub, the OSS, and the BSS for SP customers.

Figure 4-3: Representation of the HNM functions



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4.6 Moving Base Station Architecture As Moving Base Station (MBS) we refer to radio access and SANSA-complied mobile backhauling

infrastructure installed on a moving platform, such as a cruise ship. By SANSA-complied mobile

backhauling infrastructure we mean an iBN which enables both satellite and terrestrial mobile

backhauling.

The radio access segment is comprised of either Wi-Fi hotspots or LTE (H)eNBs (e.g. small cell). These

are connected through optical fibres to the iBN. Often, a concentrator is placed between the radio

access nodes and the iBN. Its role is to gather the traffic from the radio access nodes and transfer it

to the iBN. The radio access network may have its own network management system (NMS) for

operation and maintenance (O&M) purposes. Such a setup is shown in Figure 4-4.

Figure 4-4: Moving base station architecture



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5. Definition of Key Performance Indicators

5.1 Objectives The objective of this section is to define the end-to-end key performance indicators (KPIs) that are

going to be used in order to evaluate the performance of the SANSA backhaul network solution.

The KPIs defined for SANSA refer to the overall performance of the solution and reflect the

objectives of the project focusing on the areas of improvement. The requirements imposed on the

SANSA enabling components as a consequence of the KPIs are out of the scope of this document and

will be presented in D2.4 “Requirements specification for the key enabling components”.

The end-to-end KPIs that will be assessed for SANSA are the following:

Aggregated throughput

Backhaul network resiliency

Delay

Spectrum efficiency

Energy efficiency

Geographical coverage

It should be pointed out that the project does not aim to improve delay, however it is included as a

KPI to ensure compliance with current expected performance. The assessment of delay and bit error

rate is based on the user perspective and the type of service that is delivered. SANSA shall employ all

the necessary mechanisms to adapt the backhaul network and fulfil these requirements. This topic

will be studied in depth in WP4 where we will be looking at the different traffic classification, load

balancing and routing algorithms.

In the sections that follow we present the end user Quality of Sevice (QoS) requirements for the

different types of service, define the system end-to-end KPIs, and set the corresponding target

values.

5.2 End user QoS requirements per service type ITU-T has introduced the G.1010 Recommendation which defines the user-driven performance

requirements for different types of service that are independent of the underlying technology and

network used [14].



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The main parameters that impact the user’s perceived quality of service are:

Delay: The delay perceived by the user is the time it takes between the request and delivery

of information. The achieved throughput is also taken into consideration here, as the user

perceives its impact on the experienced delay. Delay is a very important parameter that

influences the user satisfaction of the service and it is highly dependent on the service type.

Delay variation: The experienced delay is not always fixed, but it varies over time. Delay

variation can be mitigated in delay-sensitive applications with the use of buffering. However,

buffering may result to additional delay being added to the user experience, affecting the

perceived QoS.

Information loss: In all types of service information loss is directly linked to the quality of

information received by the user and is therefore a key requirement.

The following service types are highlighted in [14] with a detailed breakdown of their quality levels in

[15].

Conversational voice: This category includes all services that need to relay voice irrespective

of the technology used. All three parameters of delay, delay variation and information loss

present challenges for this service type. Delay can cause echo which is usually solved with

echo cancellers. High delay can also make the conversation difficult when it starts becoming

noticeable by the conversing parties. The human ear is sensitive to delay variance so it is

common practice to use buffers to remove the variation among the arrival of the different

packets. Lastly, it is important for the information loss to be kept at a level that doesn’t

affect the natural sound of the human voice so it can be easily recognised.

Voice messaging: Voice messaging is different to the conversational voice in the sense that it

is not real-time communication so the delay requirements can be relaxed. In this context,

delay is referring to the time between requesting to record or replay a voice message and

the starting to do so.

Streaming audio: The main requirement when streaming audio is to maintain high quality

while reducing the need for re-buffering at the receiver. Information loss is less critical than

for conversational voice (since retransmissions are possible) but more important than for

voice messaging in order to maintain uninterrupted audio flow. As with voice messaging,

there is no requirement for interactive communications so the user can tolerate higher

delays. However, unlike voice messaging audio streaming can be subject to re-buffering

which impedes the overall quality of experience.

Videophone: This service combines two-way video and audio communication such as Skype



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video call or other video conferencing applications. Due to the conversational nature of this

service, the user requirements are the same as in conversational voice applications in terms

of delay, however there is an additional requirement for lip-synch which refers to the

synching between the audio and video traffic. As far as quality is concerned, the information

loss rate achieved should be better than that for the conversational voice as both video and

audio is included in this service.

One-way video: This service is equivalent to streaming audio so the user requirements are

similar.

Web browsing: Web browsing refers to accessing the HTML content of webpages and the

main indicator is the time between requested and viewing the desired content. Therefore,

the delay is more tolerable compared to videophone or conversational voice.

Bulk data transfer/retrieval: As this type of service refers to file downloading, the user can

be more lenient with the delay requirements especially as the size of the downloaded file

increases.

High priority transaction services: High priority transactions are the ones required for e-

commerce such as online payments. The delay for these should be similar to that for web

browsing because the user needs to feel confident about the responsiveness of the system.

Low priority transaction services on the other hand are primarily one-way (such as SMS

service) and can function with much higher delays of up to 30s.

Command/control: Very low delay and no information loss are the key requirements for

command/control applications as the majority of these services are time critical. Interactive

gaming is a type of such applications with very strict delay requirements to ensure the

desired quality for the user.

Still image: There is a variety of encoding formats for still images with different

requirements for information loss. The delay expected from the user is comparable to the

one for file transfers.

E-mail access: The main requirement for email access is the responsiveness of the local

server to the user requests. In this context, the delay that can be tolerated by the user is a

few seconds whereas the server-to-server communication can take several minutes.

Figure 5-1 classifies the different service types presented based on their delay and information loss

requirements.



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Figure 5-1: Model for user-centric QoS categories [14]

Based on the characteristics of the different types of service that were described, Table 5-1

summarises the performance targets for the various audio, video and data applications. It should be

pointed out that these targets are set based on the end user perception of the QoS, so they are not

linked with any specific underlying technology. For most services preferred and acceptable targets or

limits are available which helps to evaluate whether a specific technology can be employed for a

specific service. This model is a good fit for the SANSA backhaul network because it enables us to

evaluate the performance of every service based on the actual user needs, map it to the available

terrestrial and satellite links and select the best solution. Throughout the project though, it will not

be possible to evaluate the performance of all the services presented below, but only the

performance of a number of representative services.

Table 5-1: Performance targets for audio, video and data applications [14]

Application Description Key Performance Parameters

Medium Application Degree of symmetry

Typical data rates/Amount of data

One-way delay Delay variation

Information loss

Audio Conversational voice

Two-way 4-64 kbit/s Preferred < 150 ms Limit = 400 ms

1

< 1 ms < 3% PLR

1 These delay figures assume echo control mechanisms.



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Information loss

Audio Voice messaging Primarily one-way

4-32 kbit/s Playback < 1 s Record < 2 s

< 1 ms < 3% PLR

Audio High quality streaming audio

Primarily one-way

16-128 kbit/s < 10 s << 1 ms < 1% PLR

Video Videophone Two-way 16-384 kbit/s Preferred < 150 ms

2

Limit = 400 ms < 1% PLR

Video One-way video One-way 16-384 kbit/s < 10 s

< 1% PLR

Data Web browsing Primarily one-way

~10 KB Preferred < 2 s/page Acceptable < 4 s/page

N/A Zero

Data Bulk data transfer/retrieval

Primarily one-way

10 KB-10 MB Preferred < 15 s Acceptable < 60 s

N/A Zero

Data Transaction services - high priority

Two-way < 10 KB Preferred < 2 s Acceptable < 4 s

N/A Zero

Data Transaction services - low priority

Primarily one-way

< 10 KB < 30 s N/A Zero

Data Command/control Two-way ~1 KB < 250 ms N/A Zero

Data Still image One-way < 100 KB Preferred < 15 s Acceptable < 60 s

N/A Zero

Data Interactive games Two-way < 1 KB < 200 ms N/A Zero

Data Telnet Two-way (asymmetric)

< 1 KB < 200 ms N/A Zero

Data E-mail (server access)

Primarily one-way

< 10 KB Preferred < 2 s Acceptable < 4 s

N/A Zero

Data E-mail (server to server transfer)

Primarily one-way

< 10 KB Can be several minutes

N/A Zero

2 Additional requirement for lip synch delay < 80 ms.



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Information loss

Data Fax ("real-time") Primarily one-way

~10 KB < 30 s/page N/A < 10-6

BER

Data Fax (store and forward)

Primarily one-way

~10 KB Can be several minutes

N/A < 10-6

BER

Data Usenet Primarily one-way

1 MB or more Can be several minutes

N/A Zero

5.3 Definition of end-to-end KPIs

5.3.1 Aggregated throughput This KPI is directly related to the objective of the project to provide solutions that will help future

systems to keep pace with the access capacity increase towards achieving such 1000x capacity

increase in 2020.

The aggregated throughput is the sum of data plane throughput that end-users achieve. The actual

values will depend on the use case determined amongst other parameters by the number of UEs,

the redundancy level of the backhaul topology, the number of gateways to the EPC network, and the

injected traffic volumes. One of the main technologies in the SANSA solution to attain aggregated

throughput improvement will be based on a distributed intelligent routing and load balancing

functionality embedded in iBNs.

Note that the RAN and core network segment of the SANSA network will be unmodified. Thus, the

improvement of this KPI will be based on a much higher exploitation of all deployed backhaul

resources by evenly balancing the load among the available terrestrial and satellite links and by

sharing bands between the two segments. A successful outcome for this indicator will be to

demonstrate that the satellite backhaul segment becomes an essential component of future

backhaul networks through potentially both simulations and proof of concept demonstrations.

5.3.2 Backhaul network resiliency Backhaul network resiliency is one of the core project objectives and therefore an important KPI for

the performance assessment of the SANSA solution.



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Resiliency in the context of SANSA refers to the ability of the whole terrestrial-satellite hybrid

backhaul network to adjust its backhaul topology to overcome events of link failure and/or

congestion with the end goal of providing consistent high QoS to the end users. The solution

provided by SANSA is twofold; reconfiguration of the terrestrial links by the centralized HNM to

allow skipping unusable backhaul links, and reconfiguration of satellite/backhaul resources to

provide a reconfigured topology for the mobile backhaul traffic. It is also important to note that the

SANSA solution also encompasses intelligent forwarding techniques embedded in the iBNs for the

reconfiguration of routes on a distributed way to quickly react under congestion and/or link/iBN

failures.

The key enabling component for the network topology reconfiguration is the central HNM as

presented in Section 4.5. The reconfigurability capabilities of the HNM will be demonstrated through

a proof of concept for the HNM in 5 different scenarios of link failure and/or congestion. The results

of the relevant HNM demonstrations will be presented in WP5. The actual value to measure

backhaul network resiliency will mainly depend on the magnitude of the network failure event (e.g.,

route failure, link congestion, link failure, node failure, portion of the backhaul network experiencing

failures) and whether it can be managed in a distributed way or in a centralized way with the

involvement of the HNM. In the former case, the reaction time will be in the order of cents of

milliseconds and it will not involve the reconfiguration of backhaul resources (e.g., topology), but the

reconfiguration of some decision autonomously taken by the iBNs (e.g., a change in the routing

decision). In the latter case, the reaction time will be in the order of seconds and the measurement

will integrate the time devoted to take a decision at the HNM and the time devoted to take the

action triggered by such a decision (e.g., reconfiguration of backhaul resources).

5.3.3 Delay Delay is one of the most important parameters for end user satisfaction and it can be defined as the

response time of a service perceived by the end user. As presented in Section 5.2 every type of

service has different delay requirements based on its functionality and use case.

Although SANSA’s main goal is not to improve delay, it is important to ensure that user requirements

for delay are being fulfilled and that the proposed solution does not increase the perceived delay by

the end user. Furthermore, the SANSA solution will aim to lower backhaul delays, especially under

backhaul scenarios in which there are enough backhaul resources deployed to do so. One of the

main components in the SANSA solution helping to attain delay improvements will be the distributed

intelligent routing and load balancing functionality embedded in iBNs.

Note that as with throughput the actual measured values will highly depend on the measured SANSA

scenario. In particular, the traffic load injected in the network, the number of hops required to

traverse the backhaul are some parameters determining the actual delay values.



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5.3.4 Spectrum efficiency One of the project targets is to achieve a 10-fold spectral efficiency improvement within the

considered Ka band segments.

Spectral efficiency ((bits/sec)/Hz) is defined as the ratio of the data rate transmitted over a specific

bandwidth to the bandwidth itself. It is a measure of how efficiently a limited frequency spectrum is

utilized by a physical layer scheme.

SANSA aims to develop novel interference mitigation techniques that will allow deploying satellite

terminals dedicated to backhaul operations in the 17.7-19.7 GHz band without the need of

occupying part of the satellite exclusive bands. In a similar way, they will be also deployed in the

exclusive terrestrial sub-bands within the 27.5-29.5 GHz. Spectrum efficiency in the project context

is the ability to exploit the shared Ka bands for delivering mobile backhaul services.

5.3.5 Energy efficiency As the energy consumption of communication network infrastructure is growing, the SANSA solution

aims to achieve energy savings up to 30% compared to the energy consumption of the benchmark

solutions.

The mechanism that SANSA will employ to improve energy consumption will be built into the traffic

management algorithm that will enable specific nodes to go into sleep mode based on current

topology and traffic demands. The improvement will be showcased through simulations of the traffic

management algorithm applied on different instantiations of backhaul topologies.

5.3.6 Population coverage Another SANSA objective is to facilitate the deployment of mobile networks in sparsely populated

areas. This is currently a challenge for the MNOs as the cost of deploying network infrastructure in

remote areas is high and is difficult to justify with the size of the addressable market in these areas.

Coverage can refer to either population, i.e. the percentage of population that can access a service,

or to geographic coverage, referring to the percentage of geographic area where a service is

available. In the context of SANSA we refer to population coverage in the EU member states and the

target set is to demonstrate 95-99% coverage.

By demonstrating that the SANSA key enabling components and the spectrum sharing techniques

enable the operation of a hybrid terrestrial-satellite backhaul network, anyone can access the

mobile services provided they are within the footprint of a Ka band satellite.

In Figure 5-2 there is a map indicating the footprint of Avanti in the EU. We can see that almost the

whole EU area is covered by Ka band satellites.



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Figure 5-2: Avanti coverage over the EU [16]

Table 5-2 shows the percentage of EU area and population covered by Avanti Hylas 1 and Hylas 2.

Table 5-2: Avanti Hylas 1 and Hylas 2 EU coverage

EU countries Area (Sq km) Population Covered by

Hylas 1?

Covered by

Hylas 2?

Area covered

(Sq km)

Population

covered

Austria 82,450 8,527,230 Yes Yes 82,450 8,527,230

Belgium 30,280 11,202,066 No Yes 30,280 11,202,066

Bulgaria 108,610 7,245,677 Yes Yes 108,610 7,245,677

Croatia 53,910 4,290,612 Yes No 53,910 4,290,612

Cyprus 9,240 865,878 No Yes 9,240 865,878

Czech Republic 77,250 10,517,400 Yes Yes 77,250 10,517,400

Denmark 42,430 5,634,437 No Yes 42,430 5,634,437

Estonia 45,339 1,294,486 No No - -

Finland 338,424 5,180,000 No No - -



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France 547,660 65,959,000 Yes No 547,660 65,959,000

Germany 348,770 80,716,000 Yes Yes 348,770 80,716,000

Greece 128,900 11,123,034 Yes Yes 128,900 11,123,034

Hungary 89,610 9,879,000 Yes No 89,610 9,879,000

Ireland 68,890 4,593,100 Yes Yes 68,890 4,593,100

Italy 294,140 60,762,320 Yes Yes 294,140 60,762,320

Latvia 62,250 1,996,500 Yes No 62,250 1,996,500

Lithuania 62,680 2,939,431 Yes No 62,680 2,939,431

Luxembourg 2,586 439,539 No No - -

Malta 320 416,055 No Yes 320 416,055

Netherlands 33,760 16,862,400 No Yes 33,760 16,862,400

Poland 304,250 38,221,000 No Yes 304,250 38,221,000

Portugal 91,500 10,477,800 Yes No 91,500 10,477,800

Romania 229,890 19,942,642 Yes No 229,890 19,942,642

Slovakia 48,100 5,415,949 Yes No 48,100 5,415,949

Slovenia 20,140 2,063,525 Yes No 20,140 2,063,525

Spain 498,980 46,507,800 Yes No 498,980 46,507,800

Sweden 410,330 9,684,858 No Yes 410,330 9,684,858

UK 241,930 64,105,700 Yes Yes 241,930 64,105,700

Total 4,272,619 506,863,439

3,886,270 499,949,414

Total (%) - -

90.96% 98.64%



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5.4 KPIs and targets The following table summarises the end-to-end KPIs of the SANSA solution as well as their targets.

Table 5-3: System end-to-end KPIs

KPI Target

Aggregated throughput Additional satellite capacity

Backhaul network resiliency SANSA reconfigured network up

and ready in <10 seconds.

Delay

Per service type targets.

Expected improvements of up to

20-30% over SoTA routing

solutions especially under

backhaul environments.

Spectrum efficiency 10-fold improvement within the

considered Ka band segments.

Energy efficiency Up to 30% improvement

compared to benchmark.

Coverage 95-99% EU coverage



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6. Identification of Research Challenges

6.1 Specific challenges associated with SANSA integrated terrestrial and satellite backhaul node

SANSA integrated and satellite backhaul node creates a number of research and technical challenges

as presented below.

6.1.1 Efficient allocation and management of resources in terms of cost and energy The existence of two links on a number of nodes is posing challenges to the efficient allocation and

management of resources. The way resources are going to be allocated, taking into consideration

the additional cost and capacity that the satellite link introduces into the system and the way this

can be balanced in order to have the most efficient use in a way that additional cost is surpassed by

the performance enhancement.

Apart from cost efficiency of the integrated backhaul link, energy efficiency is also a question within

the SANSA frame. Management of links and related equipment should make sure that those links are

used in a power efficient way as one of the major project objectives is to reduce power consumption

up to 30% compared to existing backhaul networks.

6.1.2 Investigation of handover capabilities between terrestrial and satellite backhaul nodes

As it has already been mentioned, one of the main characteristics of SANSA is the coexistence of

satellite and terrestrial links at the same node. One of the challenges created by this coexistence is

the handover capabilities of the node. Hence, the node should be able to provide this handover in a

manner transparent to the user. This means that overload and failure monitoring mechanisms

should be employed by the integrated backhaul node in order to be able to constantly identify

overloaded links and redirect traffic to the less congested ones.

6.1.3 Interoperability of the iBN One of the main challenges that SANSA project will have to deal with is the interoperability of the

terrestrial link and the satellite link. This node will have to seamlessly provide connectivity between

two totally different links, a terrestrial microwave link and a satellite link, both operating at the Ka

band. The different nature of the two links requires that the design is taking into consideration

several aspects of the heterogeneity between the satellite link and the terrestrial link. The

components, the interfaces, the routing capabilities as well as traffic classification techniques are

designed in a manner that there is no biased routing decision and the best path is selected under



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any circumstances. Moreover, careful network planning and interference management is required at

a node level in order to avoid interference.

6.1.4 Components design SANSA network promises to deliver a self-reconfigurable, smart network that will enhance backhaul

capabilities. In order to achieve the objectives set, new components will have to be developed.

These components as they were already described are the HNM, which will centrally manage the set

and the smart antenna.

6.1.5 Traffic classification One of the main SANSA features is its hybrid nature. SANSA will take advantage of both satellite and

terrestrial connections; hence a mechanism to classify traffic and send data through the optimal

connection will be needed. There are several techniques that can be applied in order to classify

traffic (port based, DSCP, policy based etc.). The decisions will be based on each service’s unique

characteristics such as bandwidth requirements, latency and jitter sensitivity. What can be told a

priori is that the satellite connections can enhance video services that are bandwidth hungry but not

latency sensitive; the type of traffic expected to be dominant in 2020 [17]. Terrestrial connections

can support services that require low latency and low jitter, like voice services. The service

requirements as expressed in the previous chapter will play a key role in the design of a traffic

classification mechanism for the hybrid network.

6.1.6 iBN interfaces with satellite and terrestrial links SANSA will use already existing equipment for the satellite and terrestrial connections. As a result

SoTA satellite modems will be used to support satellite connections. The same applies for the

equipment used to support terrestrial connections. These devices will need to communicate with

the new components, which will support the existence of the integrated backhaul node at central

and local level. Thus, the design of the interfaces to support this communication is another challenge

for the proper functionality of the integrated backhaul node.

6.1.7 iBN monitoring performance The iBN will be responsible for decisions at a local level as far as the SANSA network is concerned. As

a result, constant accurate monitoring of the network resources and link status for satellite and

terrestrial link as well as proper connection with the HNM should be designed. Real time

undisrupted monitoring of the node status (signal levels for terrestrial and satellite connections,

available bandwidth etc...) is of paramount importance.



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6.2 Specific challenges associated with SANSA smart antennas

6.2.1 Transceiver architectures In contrast to communication systems below 6GHz, SANSA terminals operating at Ka band are

expected to have a large number of antennas in order to cope with the path loss and interference

mitigation requirements. This large increase in the number of antennas leads to additional research

challenges.

Considering an operational bandwidth of 1 GHz available in the SANSA spectrum sharing scheme, an

antenna array with 50 elements would require an underlying hardware able to work at 50 GHz of

bandwidth. This bandwidth is unaffordable with the current off the shelf FPGAs and ASICs. As a

result, digital precoding and filtering becomes unfeasible in SANSA terminals even if low complexity

precoding and receiving schemes are deployed.

As a result, the system designer shall target transceiver architectures whose number of digital

entries is reduced severely. Where the beamforming is done in the analog domain, the baseband

processor would only require one digital entry, thus minimizing the hardware bandwidth processing

requirements. It is important to note that even though the beamforming operation is done in the

analog domain, its control requires certain digital inputs. For that case, and depending on the

operational mode, the transmitter shall be able to compute the analog beamforming matrix and

send it to the beamforming network. This can be the case of an analog phase only architecture

where the transmitter shall compute the different phases considering the different number of

control bits.

Unfortunately, certain operation modes required in SANSA terminals require very complex analog

units. This is the case of multibeam transmission (i.e. two different symbols simultaneously sent with

different beamformers) that require 2N phase shifters, power amplifiers and N combiners. This can

exponentially increase the analog subsystem cost and complexity.

Consequently, an intermediate solution where certain processing is done at the digital domain and

the rest in the analog one is more convenient. This way, the analog processing unit will transform N

analog signals to M digital entries, with M<N, leading to a substantial reduction of the digital

processing complexity.

The research challenges of the overall transceiver design are the following:

i) Which is the ‚optimal‘ M and N? In other words, how much processing shall be done in

the analog and digital domain.

ii) What is the most efficient analog processing unit yet preserving a low cost? i.e. ‘Phase

only array‘, ‘switching matrix’, ‘spatial feeding scheme’, etc.



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iii) Given a hybrid architecture, what are the optimal precoding/filtering digital-analog

matrices?

6.2.2 Angle Coverage Considering the large path loss inherent from the Ka-band transmission, it is essential to take into

account the height of the SANSA terminals. In contrast to sub-GHz transmissions, microwave

communication links propagation is no longer located in the same plane with antennas and is

instead distributed randomly in three-dimensional space.

Under this context, SANSA terrestrial transceivers shall be able to point in a three dimension basis.

Covering 360º degrees in azimuth and -90º to 90º in elevation can be a very challenging design. In

addition, depending on the use cases the angle coverage requirement can be reduced. For instance,

in rural scenarios where large levels of re-configurability are not expected, the antenna would need

shorter angle coverages. On the contrary, urban scenarios would require large angle coverages as

the node density will increase exponentially.

6.3 Specific challenges associated with Hybrid Network Management

6.3.1 Configuration management The HNM must encompass resource control and traffic planning functions for the hybrid network, by

interacting with iBNs. This management will happen at different time-scales. There are

reconfiguration processes taking place at small time-scale (seconds or fractions of seconds), at node

level, while other changes will be made at medium time-scale (in the order of minutes) or even at

larger scales (manual or planned network reconfigurations).

The network nodes in SANSA network can be hybrid, in the sense of having both terrestrial and

satellite terminals, and the HNM must be aware of the beams being deployed throughout the

network at any certain moment.

The number of reconfigurable antenna/modem/sat-modem/sat-hub parameters needed in the

frame of SANSA needs to be confirmed, but will probably be related to:

terrestrial beam configuration commands (using modem/antenna parameters)

satellite link bandwidth and MODCODs

6.3.1.1 Terrestrial system configuration This function consists in the configuration of the resources of the backhauling network, including not

only physical but also upper layer parameters. Modifications could be global or affecting only parts

of the topology. The difficulty lies on keeping the network stability when performing such

modifications. The amount of available network capacity is closely dependent on spectrum



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resources. If these are considered as fixed, only ‘small’ modifications can be performed in the

network to optimize efficiency, according to network conditions.

6.3.1.2 Satellite system configuration In addition to terrestrial resources, SANSA network can make use of the satellite system for network

resiliency or optimization. A GEO satellite, using Ka band, with DVB-RCS2/S2x air interface, will be

considered in SANSA. Satellite resources should be used only when the efficiency gains justify it. This

requires that the HNM periodically calculates alternative topologies with or without using the

satellite links, and their corresponding cost. Also, it could be practical for certain services, such as

CDNs, the use of the satellite component when the terrestrial resources are scarce or when better

synchronization is required (regardless of the physical terrestrial topology).

6.3.2 Frequency plan management The scope of this function will strongly depend on the frequency reuse strategy, between the

satellite and terrestrial segment. There could be reconfiguration plans including restrictions to avoid

spectrum reuse or, on the contrary, to maximize the bandwidth. Complexity for the HNM lies on

applying these policies locally, depending on cell or coverage areas location.

6.3.2.1 Interference management Several interference scenarios can be considered for SANSA, normally originated by the terrestrial

signal. Interferences can be originated from terrestrial or satellite transmitters, and may affect both

UL and DL beams. To mitigate this problem, the function of the HNM could detect interferences and

‘repair’ the network as soon as possible, by switching down the source or changing to a more secure

frequency plan.

For the satellite system, location of the interferer position could be challenging when appropriate

tools are not available at the Satellite Control Centre.

Interference from satellite DL signal to the terrestrial transmission seems not to be an issue, because

antennas are very directive.

6.3.3 Fault management The monitoring function will enable the HNM to become aware of the events in the network

topology, which may trigger automatic reconfiguration actions to continue meeting the established

KPIs:

A terrestrial or satellite beam can be switched off.

A certain node can report a congestion state, for instance when the HNM receives traffic

performance measurements.

A traffic classification strategy can be modified as a link status changes. Although this



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modification could be performed locally by the iBN, further modifications in other nodes

could be required, if not done automatically.

Static configuration actions are also foreseen in the HNM, when a new network topology is to be

defined. This operation, manually performed by SANSA operator, consists on establishing new links

or modifying existing ones. It implies nodes reconfiguration, since a new set of beams (or beams

characteristics) needs to be propagated throughout the whole network.

It is envisaged that smart antennas can reconfigure themselves to improve link conditions. In

principle, this can be done independently of the HNM stored configuration, which aims mainly to

store antenna pointing and power (or more specifically, destination nodes and bandwidth).

6.3.4 Performance management The HNM should monitor the network performance by obtaining certain subsystem indicators from

the node elements and offer global performance indicators to the operator. According to the

network size, the HNM could receive a big volume of indicators and require high processing power

to extract the system performance.

6.3.5 Network management (topologies) The HNM must implement topology reconfiguration. In principle, the implementation should be

independent of the scenario (rural, urban, etc.). This functionality will be able to define a combined

ring/tree topology, starting with a node matrix having certain constraints (e.g. each iBN can only

connect to other neighbours if they are reachable). The objective is that no nodes in the mesh

network are left un-connected, while covering all the needed area. Moreover, for topology central

nodes, the bandwidth requirements will be higher. At macro-cell level, it can be considered that links

among eNBs are fixed, and will not be configured by the HNM. The HNM will take into account

micro-cells associated to smart antennas topologies.

Other function related to topologies is the ability to respond to link failures, by using alternate

connections among iBNs. This will be possible only when there are reachable neighbour nodes that

allow for an alternate topology communication enabling to bypass the broken link. As the number of

beams from each terrestrial antenna is fixed, this operation will possibly imply to remove one

‘healthy’ link to be able to construct the alternate path(s).

One important HNM feature will be topology modification in response to traffic congestion events,

at macro/micro cell level. To this aim, it must be configured the combination of aggregated capacity

available at each iBN, considering both terrestrial and satellite links for the hybrid nodes. Satellite

links, when established, can relieve terrestrial links when congestion events happen.

The HNM must support a multicast architecture. That is, it should be able to establish both PtP and

PtMP links/beams whenever needed.



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6.3.6 Interface with the core network (EPC) Implementing user traffic interfaces between the EPC and the HNM is not foreseen in the frame of

SANSA. It can be assumed that edge nodes are directly connected via fibre links to the EPC, and

therefore to the S-GW. These nodes will be hybrid, and therefore the packets received or directed

from/to another satellite terminal will be conveniently sequenced before they are de-capsulated at

the S-GW or the eNB.

6.3.7 SANSA CDN use cases To be able to support CDNs scenario, the HNM should prepare the network to receive the multicast

contents, that is, assure that all the nodes can receive the multicast signal. This involves:

Configuring PtMP links at the regulated frequency (e.g. @18 GHz), selecting the access

scheme (normally will use TDMA/OFDMA), and using shorter link distances than those

employed for PtP links.

Decide the better multicast topology (terrestrial-only, satellite-only, hybrid). This involves

the selection of the multicast “master” node for the transmission.

Check for the best energy-saving scheme.

Configure the nodes for conveniently routing the multicast traffic, allocating resources and

routing policies where needed.

6.3.8 Mobility management This point concerns the handling of mobile terrestrial cell nodes, varying the physical topology

without HNM control. The HNM should keep track of all the cells and adapt the network topology to

maintain connectivity with the mobile or nomadic nodes. Depending on coverage, some nodes will

only be reachable through a satellite link, but other possible scenario could on a change of the

existing terrestrial links.

6.3.9 Security management The HNM must support security options for multi-profile operation (according to different roles, e.g.

a satellite operator and a terrestrial operator).

6.4 Specific challenges associated with spectrum sharing The purpose of the present report is to identify and discuss the research challenges associated with

the terrestrial-satellite spectrum sharing for purposes of backhauling. We summarize the trends in

the research community and identify open research problems.

Satellite operators are facing the spectrum scarcity of conventional C/Ku bands and they are already

demanding more spectrum in higher frequency bands. In SANSA, we focus the research effort on Ka



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band where terrestrial backhauling bands of 18 GHz and 28 GHz are shared with the satellite-to-

Earth and Earth-to-satellite, satellite bands. In doing so, terrestrial operators will be able to cope

with the increase of traffic demands and will share part of the band licensing costs with satellite

operators, whereas the latter will take part in the mobile backhaul market.

More precisely, as shown in D2.1 [1], current CEPT recommendations assign the frequency bands of

19.7-20.2 GHz and 29.5-30 GHz for exclusive Space-to–Earth and Earth-to-Space satellite

communications, respectively. The objective of SANSA is to develop novel technology that will allow

deploying satellite terminals in the 17.7-19.7 GHz band without the need of occupying part of the

satellite exclusive bands. In a similar way, they will be also deployed in the exclusive terrestrial sub-

bands within the 27.5-29.5 GHz.

Here, we focus on the research challenges associated with the spectrum sharing in hybrid satellite-

terrestrial backhauling networks. These research challenges have been classified in two general

categories: 1) Spectrum awareness techniques which focus on acquiring knowledge about the

spectrum utilization in the adjacency of a terminal, 2) Spectrum exploitation techniques which focus

on exploiting this knowledge for interference mitigation and/or resource allocation.

These two groups of techniques and the related existing literature are detailed in the following

sections.

6.4.1 Spectrum awareness techniques Spectrum awareness solutions are used to obtain relevant information and knowledge of the

surrounding radio environment.

In a first step, SANSA project will address database-assisted shared spectrum techniques to

efficiently manage the shared access to the spectrum. In addition, spectrum sensing will be explored

to improve the quality of the dynamic information stored in the databases and combined with

network-level radio environment mapping for an improved hybrid access performance.

In this section we focus our attention on research challenges associated to spectrum sensing,

spectrum cartography and radio environment mapping.

6.4.1.1 Spectrum Sensing Spectrum sensing involves making observations of the radio frequency spectrum and reporting on

the availability of spectrum. This can be done in a decentralized mode in which each intelligent

backhaul node makes a decision based on its own measurements or in a cooperative way (either

with a centralized fusion node or just sharing the information with few neighbours), in which

multiple sensing nodes cooperate [17]. The latter has been shown to be effective in relaxing the

sensitivity requirements on individual secondary users and improving the overall sensing

performance [17].



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In this section, we focus our attention in spectrum sensing challenges related to single-device

spectrum sensing methods. In SANSA context, the single-devices refer to the intelligent backhaul

nodes. Among the most important research challenges that spectrum sensing techniques must face

are [19]:

Restricted sensing ability: Most devices do not have specific RF transceiver to sense the environment and therefore they typically access the spectrum following a two-stage “listen-before-talk” protocol in which the device performs sensing and transmission independently in two different time intervals. There is an evident trade-off between the sensing capabilities and the throughput that can be achieved by these devices [20], [21].

Wideband sensing: The traditional way for sensing a wideband spectrum is channel-by-channel sequential scanning [22], which introduces large latency. One way to solve the latency problem, at the cost of implementation complexity, is to use an RF front-end with a bank of narrow band-pass filters. One of the emerging trends in the research community is to directly sense a wide frequency range at the same time [23]. Obviously, the scanning of a wide band of frequencies implies high sampling rates which are not affordable by the standard Analog-to-Digital Converter (ADC). Exploiting the fact that the spectrum of interest contains only a small number of active frequencies relative to the band-limit [24], a promising alternative to alleviate the sampling bottleneck is the use of sub-Nyquist sampling techniques also known as Compressive Sensing (CS) [25]. Wideband sensing together with CS research is known in the literature as Wideband Spectrum Sensing (WSS) and has attracted extensive attention due to its enormous potential of sharing spectral resources [26], [27].

Practical imperfections: In practice, there may occur several imperfections such as noise uncertainty, channel/interference uncertainty, and transceiver hardware imperfections like amplifier nonlinearity, quantization errors, and calibration issues [28]. These imperfections may severely deteriorate the performance of the employed spectrum awareness mechanism. In this case, investigation of the methods to counteract the effect of these imperfections is an important research challenge to be addressed from the practical perspective.

Interference measurement: This refers to the fact that one network node transmitting in a shared spectrum cannot be aware of the effect of its transmission on other active receivers operating in the same band. One possible solution is to use a separate sensor network distributed over the area of interest which captures measurements from many fixed sites to create an interference map [29]. The cooperative approach is discussed later on in Section 6.4.1.2.

6.4.1.2 Spectrum Cartography Spectrum cartography is the process of constructing a map showing radio frequency signal strength

over a geographic area (Figure 6-1). This map is commonly known as Radio Environment Map (REM)



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[30], [31]: a database containing information on the radio environment. The research challenges

related to this case are listed below:

Sharing information: REM concept is based on geo-localized measurements captured by many devices sharing the same spectrum. In such a multi-user environment, cooperation is essentialto exploit the spatial diversity. However, cooperation in the spectrum sensing phase is not straightforward since the spectrum sensing information needs to be distributed over a subset or all active devices. This might introduce delays and signalling overhead.

Decision fusion: Assuming that the sensing information is well received by all devices, another interesting research path is how to combine all the information (decision fusion algorithms) to produce an accurate map.

Learning: The REM information can be updated with observations from the cognitive nodes. Therefore, learning mechanisms and knowledge management techniques [32] which have been the objective of recent research can be applied as well in this context.

Localization of emitters: The knowledge of the emitters’ location can improve the accuracy of the final estimate of the REM. The process of REM construction becomes easier if information about the incumbent users’ locations is known beforehand by using some estimation methods [33].

Sparsity-based cartography: In general spectrum cartography literature, the spatial sparsity of the multiple sensing devices over a geographical area is not taken into account, neither the sparsity on the frequency domain of the spectrum measurements. Recent works proposed to combine CS technology with spectrum cartography to improve the Radio Environment Map (REM) construction process [34].

6.4.1.3 Spectrum awareness through regulatory databases The process of REM construction can be improved with the help of national and international

spectrum regulators, since they usually register the licensed systems into databases. The main

advantages of the availability of regulatory databases are that it can provide information about the

radio spectrum environment and hence can reduce the required sensing burden. Some challenges

related to use of regulatory databases are listed below:

Accuracy of the listed parameters: In practice, the actual values such as power levels, antenna patterns, etc., may vary from that of the specified values in the database. In such cases, databases may be considered as an initial step and it can be updated based on the outcomes of spectrum awareness mechanisms.

Temporal-variations on the spectrum use: Databases cannot capture the temporal spectrum opportunity. Again, the information provided by the database should be considered as side-information to other sensing mechanisms.

Out-of-date: Maintaining and updating of databases over time is significant for the operator. However, in SANSA, the involved terrestrial FS links and the satellite network are not



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dynamic as in a mobile system and, thus, it is not necessary to update the database so frequently. In any case, verification of available database via measurements can be considered.

Figure 6-1: Example of spectrum cartography3

3 Extracted from CROWNCOM 2010 keynote speech by Berna Sayrac (Orange Labs).



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Figure 6-2: Classification of Interference mitigation approaches

6.4.2 Spectrum exploitation techniques

6.4.2.1 Interference mitigation techniques Figure 6-2 presents the classification of several interference mitigation techniques in the context of

spectrum sharing scenarios [35]. The main techniques are: cognitive beamforming, cognitive

interference alignment, and cognitive zone. A short description about these techniques and the main

research challenges involved with these techniques are provided in the following subsections.

6.4.2.2 Cognitive beamforming The main difference between cognitive beamforming and the conventional beamforming problem

arises due to the introduction of interference constraints in order to restrict the interference

towards/from the victim/interfering stations. In this context, cognitive beamforming approaches

have been widely studied with different secondary network optimization objectives such as

SINR/rate balancing [36], [37], sum rate maximization [38], and power minimization with QoS

constraints [39]-[41].



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Cognitive beamforming can be applied in the considered SANSA scenarios with the objectives of

either controlling the interference or maximizing the SINR of the desired link. For this purpose,

additional constraints on the aggregated interference at the victim/interfering FSS stations/terminals

need to be taken into account while designing beamforming at the SANSA FS stations. Further,

depending on the spectrum sharing scenarios, either transmit beamforming or receive beamforming

or the combination of both can be investigated.

Cognitive beamforming techniques can be further applied in combination with power control [42]-

[44] and user scheduling [45]-[46][47] in order to enhance the exploitation of the unused spectral

resources. Similarly to the conventional beamforming scenarios, cognitive beamforming techniques

should be robust to the array response vector mismatch, calibration errors and channel

uncertainties. This robustness can be incorporated by employing either a stochastic or a worst case

approach [48]. Further, it is usually difficult to acquire the perfect Channel State Information (CSI)

knowledge at the secondary transmitter in practice due to limited training, less cooperation

between primary and secondary systems, and quantization issues. In this context, the aspects of

robust cognitive beamforming considering the imperfect channel state information have received

significant attention in the spectrum sharing literature [49], [50].

The main research challenges for the application of cognitive beamforming techniques in SANSA

spectrum sharing scenarios are summarized below [51].

Channel State Information: For the Channel State Information (CSI) acquisition process, investigating effective feedback techniques in order to reduce the feedback burden from the secondary/primary receivers to the secondary transmitter is an emerging research topic.

Implementation complexity: Many existing non-robust techniques may fail in creating a desired beam pattern in case of the imperfect CSI, hence causing harmful interference to the primary users. Further, there arises the issue of additional complexity while employing robustness in the beamforming design problem. To this end, the investigation of robust and practically realizable techniques is another important research challenge.

Uncertainties in the array response vector: Besides CSI robustness, beamforming solutions should also be robust to the uncertainties in the array response vector, inaccurate Direction of Arrival (DoA) information, and transceiver hardware imperfections such as phase noise, quantization errors etc.

Interference threshold: Computational efficient solutions need to be investigated in order to solve the cognitive beamforming problems in the considered SANSA scenarios.

Direction of Arrival (DoA) of devices: The acquisition of accurate DoA information of the desired and interfering sources/receivers is crucial for implementing cognitive beamforming in the considered scenario. In practice, this information can be obtained either from the databases or by employing a suitable DoA estimation algorithm.

Calibration: Accurate calibration of the antenna array equipped at the SANSA FS station is



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crucial, especially while creating nulls to the directions of the interfering/victim sources. In case of calibration errors, suitable compensation mechanisms need to be investigated.

6.4.2.2.1 Cognitive Interference Alignment In spectrum sharing context, Interference Alignment (IA) can be used as an interference mitigation

tool which aligns interference in space, time or frequency domain using suitable precoding

techniques. In this approach, signals transmitted by all users can be designed in such a way that the

interfering signals fall into a reduced dimensional subspace at each receiver. Each receiver can then

apply an interference removal filter in order to project the desired signal onto the interference free

subspace. With this phenomenon, the number of interference-free signalling dimensions of the

network can be substantially increased [52].

In the context of spectrum sharing networks, IA techniques can be broadly classified into non-

cooperative [53], [54] and cooperative [55], [56]. Further, IA techniques can be CSI-aware and blind

as depicted in Fig. 1. The main research challenges involved with cognitive interference alignment

technique are specified below [57], [58].

Channel State Information: In many cases except in the distributed IA, the global channel knowledge is required to carry out the IA operation. In this context, it’s a crucial aspect to investigate suitable blind and semi-blind IA techniques in order to reduce the overhead for acquiring the sufficient channel knowledge.

Channel uncertainty: The penalty of residual channel uncertainty at the transmitters and the impact of channel correlations are other aspects to be explored for IA implementation in practice.

Synchronization: IA techniques require strict synchronization in order to avoid any timing and carrier frequency offsets between cooperating nodes. In this context, suitable synchronization or compensation approaches need to be investigated for the realization of distributed IA in practice.

Low SNR scenarios: Investigation of new IA algorithms which can provide better sum capacity in moderate or low SNR region is another interesting research challenge [58].

Dimensionality of interference networks: Another main limitation for the IA technique is the requirement of the large dimensionality of interference networks. The practical achievable scheme which requires finite dimensions for the case of multiple non-intended receivers is still an open research problem.

6.4.2.2.2 Cognitive Zone

In the spectrum sharing scenario, a Cognitive Zone (CZ) is usually designed around the primary receiver based on its interference threshold, within which secondary users are not allowed to reuse the frequencies used by the primary user. However, in practice, the interference may occur in both directions, i.e., from the primary transmitters to the secondary receivers and from the secondary



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transmitters to the primary receiver. Depending on the considered scenarios and the level of interference between these two systems, CZs can be created around one of these receivers or both.

The CZ method has been investigated in the literature in various settings [59]-[62]. The size of the CZ has a great impact on the Quality of Service (QoS) of the primary system since it affects the level of secondary interference that needs to be tolerated and on the secondary system’s capacity since it affects the available amount of primary spectrum at a given location [62]. As depicted in Fig. 1, the CZ approach can be divided into: (i) fixed CZ, and (ii) dynamic CZ. In the first approach, the size of the CZ is fixed based on the worst case scenario, whereas in the second approach, the size of the CZ can be varied based on the time-varying information of the surrounding radio environment such as instantaneous PU behaviour. The complexity of the database for a dynamic CZ becomes higher and the adaption of the CZ is relatively a slow process depending on the level of cooperation between primary and secondary systems [63]. The main research challenges involved while applying the CZ method are mentioned below.

Unpredictable propagation conditions and inaccuracy of the database: Static CZ method may not always guarantee the perfect avoidance of the co-channel interference. The received interference level may vary based on different factors such as terrain variations, environmental conditions, achieved antenna gain patterns, etc. Since the CZ method is mostly based on database created using some propagation models, the accuracy of the database is crucial for the interference protection guarantee. Furthermore, signals could occasionally travel further than expected if (unpredictable) propagation conditions are not properly accounted for.

Terrain enabled propagation models: The consideration of the terrain-based propagation models while investigating Exclusion/protection contours in SANSA spectrum sharing scenarios is one interesting aspect to be explored.

Multi-tiered CZs: Defining the proper boundaries considering realistic propagation environment for the implementation of multi-tiered CZs in SANSA spectrum sharing scenarios is another important research challenge.

Combination of exclusion/protection zones and spectrum awareness mechanism: The sensing measurements can be considered to progressively adjust the exclusion/protection zones. How to combine these two methods effectively in the considered SANSA spectrum sharing scenarios is another interesting aspect.

Combination of exclusion/protection zones and resource allocation strategies: CZ method can be further combined with the power control approach in order to exploit the unused spectral resources in an efficient manner. Another promising approach is to combine this method with the carrier allocation method in which the secondary users within the CZ (designed for a particular frequency) can switch their operating frequency to some exclusive frequency. In this context, investigation of suitable joint approaches is another aspect which



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can be considered in SANSA spectrum sharing scenarios.

6.4.2.3 Optimization of spectrum and radio resources The resource allocation in both the communication networks and in the wireless backhaul plays an

important role in enhancing the overall system performance. On top of the interference mitigation

schemes, the resource allocation in spectrum sharing based networks is responsible for

distributing/allocating the available spectrum in combination with applying the adequate power

control strategies. In that sense, the scarce wireless backhaul frequency spectrum should be

allocated wisely so that no spectrum waste is caused due to more spectrum being allocated than

what is required. At the same time, the allocated spectrum for backhauling should not be

inadequate which would degrade the system performance significantly. The research challenges

related to the resource allocation in spectrum sharing context can include the limitation generated

from:

Imperfect spectrum sensing information: Designing the resource allocation algorithm while considering that the sensing information is perfectly known may lead to inefficient distribution of the resources and cause harmful interference to the parties that share the spectrum. Any allocation process should consider the sensing false alarm probability where the amount of the resulted interference should be adapted accordingly.

Imperfect channel state information: There is always some uncertainty in the channel state information due to the feedback channel errors, limitation, or unreliability. Accordingly, the resource allocation in the SANSA transmitters should be developed in order to reduce the negative impact of the lack of this information.

Cross-Layer resource allocation: While independent optimization per individual layer can lead to system performance improvement, exploiting the synergies between several layers may result to even better enhancement and adaptability to the system variations. Accordingly, SANSA backhauling nodes can take into account several sets of information from the MAC and network layers, in addition to the possible environmental and traffic changes.

Priority consideration: Design of well-defined utility functions to balance the different constraint and enable the usage of machine learning schemes in addition to game theoretical model can be a possible approach depending on the nature of the optimization requirements.

Computational complexity and green communications: In addition to the minimization of the transmit power, the design of an efficient resource allocation algorithm with low computational complexity helps in reducing the processing time for the backhauling nodes and accordingly reducing the latency and the consumed energy.

Inter-network interference consideration: Depending on the sharing schemes and on the way of distributing the spectrum, i.e. centralized, distributed or cluster-wise, the



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interference between the different SANSA nodes should be included considering the different possible interference caused by the communication between the terrestrial nodes and/or the communication between the satellite and terrestrial nodes.

6.5 Specific challenges associated with integrated backhaul service delivery

The service delivery model is a challenging area for the operators. The ownership of the components

and the business model needed to decide who is running the service, who is the owner of the Hybrid

Network Manager, and how data from backhauling network can access the core network. The

different approaches are a matter of the network architecture design, where the various

components will be placed and where the connection to the core network will be implemented.

Various fields of research depend on the way the service is going to be delivered and by the route

data is going to follow to access the internet.

6.5.1 Mobile terrestrial operator lead In this model, the responsible for the connectivity between the backhaul network and the core is the

terrestrial operator. The PGW, the SGW, and the HNM are entities that are present in the MNO

network. Satellite operator receives data coming from terrestrial nodes and routes them through its

network to the MNOs network. All the data handling in terms of PGW, SGW and HNM is performed

at MNO’s premises.

In order to briefly describe this scenario, data packets from the HeNB, are directed through either

the terrestrial or the satellite link following the path that was decided at the node. This decision is

the result of the interoperability function. If data flow is routed terrestrially, then all packets are sent

directly to the MNO network following the path designed by the routing algorithm. This decision will

be based on the current topology status and QoS requirements as they will be provided from the

HNM to each smart node.

If the data is sent via satellite, it is received by the satellite hub and sent to the IP gateway. From

there it is routed to the MNO’s network where the SGW and PGW are present to onwards route it to

the internet.

In this scenario all important components belong to the mobile network operator as well as the

HNM, which is responsible for the routing and topology rearrangements. The satellite operator is

transparent or almost transparent to the packets routed through its network (Figure 6-3).



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Figure 6-3: Terrestrial Operator Lead

6.5.2 Hybrid Terrestrial Satellite Operator Service The second service model is the model where satellite operator and MNO are accessing the internet

separately. This is a hybrid model since components like the PGW and the SGW are present in both

satellite and mobile network operator premises. This allows data to access the network directly

either through the satellite operator or the mobile network operator. The HNM is placed again at

the MNO’s premises and all the SANSA network management and configuration is performed by the

terrestrial operator. This model offers a wide field for virtualization research for entities like the

PGW and the SGW. The level at which PGW and SGW are going to be migrated to the satellite

operator’s network is a challenge. Big challenge is if images of these entities going to be identical to

the original ones and if users are going to have the same rights and same type of access to the

functionalities that PGWs and SGWs provide (Figure 6-4).



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Figure 6-4: Hybrid terrestrial satellite operator network

6.5.3 Satellite operator service This scenario is where the satellite and the mobile operator share the same network. This practically

means that either the satellite operator has employed mobile capabilities, or the mobile operator

has its own satellite gateway, or that a third operator (maybe a joint scheme) is running a common

network. In this scenario all components, satellite, terrestrial and SANSA are part of the same

network. The common network is where all functionalities are run. Data either from satellite or from

terrestrial links, HNM, satellite GW and hubs IP GW, PGW, SGW, MME, NCC as well as billing entities

are part of the same network. Internet access is provided here (Figure 6-5).



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Internet

SA

SA

SA

SA

SA

IBN

IBN

GW + Hub

Redundant GW + Hub

IP Gateway

NCC

NMS/OSS

SGW

PGW

MME

HNM

PCRF

Figure 6-5: Satellite lead service



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7. Conclusions

This deliverable defined the scenarios, topologies, end-to-end system architecture, end-to-end KPIs

and research and technical challenges that will feed into the subsequent WPs.

More specifically, in Chapter 2, after defining the terms use case, scenario and topology; the basic

use cases were identified. These were resilience, offloading, new nodes deployment/incorporation,

CDN incorporation and remote cell connectivity including isolated cells and moving platforms. The

significance of the periodicity of the traffic was also identified. More specifically, three types of

periodicity were identified; periodic, semi- periodic and rarely occurring events. These use cases

were the drivers that led us to the definition of the scenarios.

In the next chapter, Chapter 3, a scenario selection matrix was developed and the most relevant

scenarios were selected. The main distinction is between urban, rural and moving base station

scenarios. In total 6 scenarios were selected: two cases for the rural scenarios, three cases for the

urban and a single case for the moving base station. In order to proceed with our analysis in the

forthcoming WPs, we also used a rural topology (Helsinki suburbs) and an urban one (Vienna). A

preliminary interference analysis on these two topologies was presented along with their network

connectivity matrix. This will form the basis for the next WPs where different scenarios will be used

to investigate issues around spectrum sharing, network design as well as in the key enabling

components design.

Chapter 4 provided an end-to-end system architecture presentation that included the EPC building

blocks (like the PGW, the SGW, the HSS and the MME). The iBN and HNM were also identified as two

really important and innovative components of the SANSA end-to-end system architecture. The

design of the SANSA system architecture will rely on existing LTE elements with the addition of the

key enabling components.

KPI definition and a first assessment of the expected results in terms of performance for a series of

indicators were provided in Chapter 5. Aggregated throughput, backhaul network resiliency, delay,

spectrum efficiency and energy efficiency are among the selected KPIs that will be used to evaluate

system performance in the simulations and in the Over-The-Air demonstration.

Finally, in Chapter 6, the main research challenges posed by this project were discussed. Integrated

terrestrial and satellite backhaul node is one of them, while the Smart Antenna design and the way

they it is going to cover specific areas and connect with existing RF transceivers is another. The

design of the central entity that will control the network configuration, the Hybrid Network

Manager, is one of the important research challenges. The interference mitigation and spectrum

sharing techniques are also one of the challenging parts of the SANSA network design. Last but not



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least is the way service is going to be delivered i.e. who between the terrestrial and satellite

operators is going to be the one that allows access to the core and owns the components.



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A. Appendix

1. Notations in Table 3-11

Terrain data is from www.geocomm.com

Link_No = Link Number.

Node_Tx = Transmitting Node.

Node_Rx = Receiving Node.

Longitude_Tx = Longitude of the Transmitting Node.

Longitude_Rx = Longitude of the Receiving Node.

Altitude = Altitude of the Transmitting Node.

Elevation = Elevation of the Transmitting Node.

TxFreq = Frequency of the Transmitting Node.

RxFreq = Frequency of the Receiving Node.

BW = Transmission Bandwidth.

GainMax = Maximum gain of the transmitting antenna.

Height = Height of the transmitting antenna.

2. Satellite Link Budget When designing the satellite link budget it is really important to define the reference satellite, the

reference equipment and the point on the satellite beam in order to be able to define exactly the

needs for the link budgeting.

The satellite carrier bandwidth is one of the variables used to define the different scenarios. Three

options for the satellite channel bandwidth that correspond to different satellite communications

technologies have been identified:

Case 1 (SOTA): DL 54 MHz, UL 9 MHz

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Case 2 (Next Generation HTS): DL 441 MHz, UL 21.7 MHz

Case 3 (Ultra Wide Band): DL 230 MHz, UL 9 MHz

We have selected to run a point-to-point link budget using Hylas 1 as the reference satellite. We

randomly selected a location in Thessaloniki in Greece which can be seen in Error! Reference source

not found.. The specific point was selected to be at an appropriate distance from the centre of the

spot beam serving it.

Figure A-1: Location of the satellite terminal for point-to-point link budget

The equipment used at the remote location was a 75cm dish with 3W BUC and a Newtec satellite

router using DVB-S2 for the FWD link and DVB-RCS for the RTN link.

The carrier bandwidth assigned for the FWD link was 54 MHz. The link budget details for the best

performing MODCOD is presented in Figure A-2.



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Figure A-2: Details for the best performing MODCOD in the satellite link budget



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3. Terrestrial to terrestrial

This subsection describes the interference power levels of interference between two terrestrial links

both at 18 GHz and 28 GHz. We will consider 3 different relative positions (azimuth and elevation)

and 3 distances, leading to a total number of 9 interference power levels. It is important to remark

that azimuth and elevation angles have been considered the same in order to reduce the use case

repetitions.

In addition, considered directivity values have been obtained from the spectrum regulation in Fixed

Radio Systems; Multipoint Equipment and Antennas; Part 3: Harmonized EN covering the essential

requirements of article 3.2 of the R&TTE Directive for Multipoint Radio Antennas for the 28 GHz case.

For the 18 GHz case we assume the same spatial mask

Table A-1: Directional Antennas (linear polarization) from 24.25 GHz to 30 GHz, types DN1 to DN5

28 GHz directivity regulation values.

The considered scenario is a radio link in a distance of 1 Km where an interfering link is

positioned at 1, 0.5 and 2 Km distance. Additionally, we consider 4 angle positions 0, 8, 30

and 90 degrees based on the spatial mask presented before. The reference system has an

SNR of 62 dBs with a noise power level of -88 dBm.

The following table depicts the resulting SINR values of the different sub-scenarios.

Table A-2: SINR values of the different sub-scenarios

Distance [Km]/Angle [º] 0 8 30 90

1 0,0 17,0 22,0 30,0

0,5 -6,0 11,0 16,0 24,0

2 6,0 23,0 28,0 36,0



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In light of the above table it is evident that the terrestrial links decrease the achievable rates

severely even if low angles are considered. This motivates the use of smart antenna

technology of mitigating the interference power levels both at the transmit and receive

parts. For the sake of completeness, we include the interference power levels in the

following table

Table A-3: Interference power levels

Distance/Angle 0 8 30 90

1 -27 -44 -49 -57

0,5 -21 -38 -43 -51

2 -33 -50 -55 -63

4. 18 GHz Link Budget (CTTC)

The following link budget has been done assuming the equipment described in

http://www.proxim.com/products/point-to-point-backhaul/tsunami-gx810. We will consider the

following:

Table A-4: Parameters for the 18 GHz terrestrial link budget

Parameter Value

Transmit power 30 dBm

Bandwidth 60 MHz

Receiver sensitivity

QPSK (-85.5 dBm)

32QAM (-74.4 dBm)

256-QAM (-66 dBm)

Antenna gain 30 dBi

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The distance between the different base stations is assumed to be between 1 and 5 Kms. In the

following, we show the link plots for each scenario. As it can be observed in the different plots, there

is a sufficient SNR margin. Indeed, in case we would like to operate at the highest rate, the SNR

margin becomes 24 dBs in the 5 Km case.

Figure A-3: Terrestrial link budget for 1 Km distance at 18 GHz

-100

-80

-60

-40

-20

0

20

40

60

80

TX TX Ant RX Ant RX

-100

-80

-60

-40

-20

0

20

40

60

80

TX TX Ant RX Ant RX



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Figure A-4: Terrestrial link budget for 5 Km distance at 18 GHz

The next table summarizes the overall link budget:

-100

-80

-60

-40

-20

0

20

40

60

80

TX TX Ant RX Ant RX

-100

-80

-60

-40

-20

0

20

40

60

80

TX TX Ant RX Ant RX



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Table A-5: Terrestrial link budget

RF System (Link Budget) Calculations

System Variables Variable Units Equation Value

Frequency f0 MHz

18000

Speed of Light c m/s

299792458

Wavelength λ m λ = c/f0 0,016655137

Block Variable Units Equation Value

PA Power PPA dBm

30

TX Match Loss LMatchT dB

TX source PTX dBm

30

TX connector loss LConT1 dB (from Connector Loss sheet) 0

TX cable loss LCabT dB (from Cable Loss sheet)

TX connector loss (remote antenna) LConT2 dB (from Connector Loss sheet)

TX power PT dBm PT = PTX(C&C Loss) 30

TX antenna gain GT dBi

30

Effective (Isotropic) Radiated Power EIRP dBm EIRP = PT GT 60

Distance d m

5000

Channel Medium Loss Factor L0 dB (from Medium Loss sheet) 0

Free Space Loss LFS dB LFS = (λ/4πd)2 -131,5326334



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Power at RX Antenna, Free Space Path PChanFS dB PChanFS = LFSL0 EIRP -71,53263341 Flat Earth Loss (Includes Ground

Bounce) LFE dB (from Ground Multipath sheet) -128,9436901

Multipath Loss LMP dB

Obstruction Loss LObs-Total dB

0

Power at RX Antenna, Flat Earth Path PChanFE dB PChanFE = LFEL0LMPLObs

EIRP -68,94369013

RX antenna gain GR dBi

30

RX connector loss LConR1 dB

0

RX cable loss LCabR dB

0

RX connector loss (remote antenna) LConR2 dB

0

RX power, Free Space Path PRFS dBm PRFS = PChanFS GR(C&C

Loss) -41,53263341

RX power, Flat Earth Path PRFE dBm PRFE = PChanFE GR(C&C

Loss) -38,94369013

-66

Sensitivity of Rx

Receiver Sensitivity Calculations Variable Units Equation Value

RX Noise Figure NF dB

7

Operating Temperature T0 K

290

Effective Noise Temperature Te K Te = T0(NF - 1) 1163,442978

Boltzmann's constant k J/K

1,38E-23

Receive Bandwidth BWRX MHz

60

Antenna Temperature TAnt K

300



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Noise Power (at RX) Pn dBm Pn = k(TAnt + Te)BWRX -89,16593858

Interference Power In dBm

-1000

Signal to Noise Ratio SNIRRX dB SNIRRX = PRX/(Pn + Pi) 47,63330517

23,16594

Minimum SNIR

24,46737

Margin

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D2.3 Definition of reference scenarios, overall …...D2.3: Definition of reference scenarios, overall system architectures, research challenges, requirements and KPIs Date: 01/02/2016