The SON (Self-Organizing Networks) Ecosystem: 2015 – 2030 – Opportunities, Challenges, Strategies & Forecasts

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Date: 13-Aug-2015
No. of pages: 180
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SON (Self-Organizing Network) technology minimizes the lifecycle cost of running a mobile network by eliminating manual configuration of equipment at the time of deployment, right through to dynamically optimizing performance and troubleshooting during operation. This can significantly reduce the cost of the operator’s services, improving the OpEx to revenue ratio.

Amid growing demands for mobile broadband connectivity, mobile operators are keen to capitalize on SON to minimize rollout delays and operational expenditures associated with their ongoing LTE and HetNet deployments.

Originally targeted for the RAN (Radio Access Network) segment of mobile networks, SON technology is now also utilized in the mobile core and transport network segments. Furthermore, the SON ecosystem is increasingly witnessing convergence with other technological innovations such as Big Data, predictive analytics and DPI (Deep Packet Inspection).

Despite challenges relating to implementation complexities and multi-vendor interoperability, SON revenue is expected to grow to more than $4 Billion by the end of 2017, exceeding conventional mobile network optimization revenue by nearly 60%.

The “SON (Self-Organizing Networks) Ecosystem: 2015 – 2030 – Opportunities, Challenges, Strategies & Forecasts” report presents an in-depth assessment of the SON and associated mobile network optimization ecosystem including key market drivers, challenges, OpEx and CapEx savings potential, use cases, SON deployment case studies, future roadmap, value chain, vendor analysis and strategies. The report also presents revenue forecasts for both SON and conventional mobile network optimization, along with individual projections for 7 SON submarkets, 6 regions and 15 countries from 2015 through to 2030.

The report comes with an associated Excel datasheet suite covering quantitative data from all numeric forecasts presented in the report.

The report covers the following topics:


  • Conventional mobile network planning & optimization

  • SON technology and architecture

  • Key benefits and market drivers of SON

  • Challenges to SON adoption

  • SON use cases

  • SON deployment case studies

  • Future roadmap of the SON ecosystem

  • Company profiles and strategies of over 70 SON ecosystem players

  • OpEx and CapEx saving analysis of SON

  • Wireless network infrastructure spending, traffic projections and value chain

  • Convergence of SON with Big Data, predictive analytics and DPI

  • Strategic recommendations for SON solution providers, wireless infrastructure OEMs and mobile operators

  • Market analysis and forecasts from 2015 till 2030


Historical Revenue & Forecast Segmentation
Market forecasts and historical figures are provided for each of the following submarkets and their subcategories:

Mobile Network Optimization


  • SON

  • Conventional Mobile Network Planning & Optimization


SON Network Segment Submarkets


  • RAN

  • Mobile Core

  • Mobile Backhaul & Transport


SON Architecture Submarkets


  • C-SON (Centralized SON)

  • D-SON (Distributed SON)


SON Wireless Network Generation Submarkets


  • 2G & 3G

  • 4G & Beyond


Regional Markets


  • Asia Pacific

  • Eastern Europe

  • Latin & Central America

  • Middle East & Africa

  • North America

  • Western Europe


Country Markets


  • Australia

  • Brazil

  • Canada

  • China

  • France

  • Germany

  • India

  • Italy

  • Japan

  • Russia

  • South Korea

  • Spain

  • Taiwan

  • UK

  • USA


Key Questions Answered

The report provides answers to the following key questions:


  • How big is the SON and mobile network optimization ecosystem?

  • How is the ecosystem evolving by segment and region?

  • What will the market size be in 2020 and at what rate will it grow?

  • What trends, challenges and barriers are influencing its growth?

  • Who are the key SON vendors and what are their strategies?

  • What is the outlook for QoE based SON solutions?

  • What is the outlook for C-SON and D-SON adoption?

  • What is the outlook for SON associated OpEx savings by region?

  • How will SON investments compare with those on traditional mobile network optimization?

  • What opportunities exist for SON in mobile core and transport networks?

  • How will SON use cases evolve overtime in 3GPP releases?

  • Which regions will see the highest number of SON investments?

  • How much will mobile operators invest in SON solutions?


Key Findings

The report has the following key findings:


  • Despite challenges relating to implementation complexities and multi-vendor interoperability, SON revenue is expected to grow to more than $4 Billion by the end of 2017, exceeding conventional mobile network optimization revenue by nearly 60%

  • SNS Research estimates that SON can enable mobile operators to save nearly 40% of their electrical power consumption by dynamically activating and deactivating RAN nodes in line with the changing traffic and user distribution profile

  • SNS Research estimates that a Tier 1 mobile operator can save more than 30% of its overall OpEx by employing SON across the RAN, mobile core and transport segments of the network

  • Mobile operators have reported up to a 50% reduction in dropped calls and over 20% higher data rates with SON implementation

  • SON platforms are moving from reactive systems to more advanced implementations that incorporate predictive analytics technology to make necessary changes to a network before any degradation occurs

  • Infrastructure and software incumbents are aggressively eyeing acquisitions of smaller established C-SON players to accelerate their entry path into the C-SON market


List of Companies Mentioned


  • 3GPP (Third Generation Partnership Project)

  • Accedian Networks

  • Accuver

  • Actix

  • Aepona

  • Aexio

  • AIRCOM International

  • AirHop Communications

  • Airspan Networks

  • Alcatel-Lucent

  • Amdocs

  • Anite

  • Arcadyan

  • Argela

  • Aricent

  • Arieso

  • ARItel

  • Ascom

  • Astellia

  • AT&T Mobility

  • ATDI

  • Avago Technologies

  • Avvasi

  • Beeline Kazakhstan

  • BLiNQ Networks

  • Broadcom Corporation

  • Bytemobile

  • Cavium

  • CBNL (Cambridge Broadband Networks Limited)

  • Celcite

  • CellMining

  • Cellwize

  • Celtro Communications

  • CENTRI

  • Cisco Systems

  • Citrix Systems

  • Comarch

  • CommAgility

  • Commsquare

  • Coriant

  • Datang Group

  • Datang Mobile

  • ECE (European Communications Engineering)

  • Eden Rock Communications

  • Ericsson

  • ETRI (Electronics and Telecommunications Research Institute)

  • Flash Networks

  • Forsk

  • Freescale Semiconductor

  • Fujitsu

  • Globe Telecom

  • Guavus

  • Hitachi

  • Huawei

  • InfoVista

  • Ingenia Telecom

  • Intel Corporation

  • InterDigital

  • Intucell Systems

  • ip.access

  • JDSU

  • KDDI

  • Lavastorm

  • Lemko Corporation

  • Mentum

  • MIMOon

  • Mobilicity

  • Mobixell

  • NEC Corporation

  • NetScout Systems

  • Newfield Wireless

  • NGNM (Next Generation Mobile Networks) Alliance

  • Nokia Networks

  • NXP Semiconductors

  • Optimi

  • Optulink

  • P.I.Works

  • Plano Engineering

  • Qualcomm

  • RADCOM

  • Radisys Corporation

  • Reverb Networks

  • Rogers Communications

  • Rohde & Schwarz

  • Rorotika

  • R-TRON

  • Samsung Electronics

  • Schema

  • SEDICOM

  • Siklu Communication

  • Singtel (Singapore Telecommunications)

  • SK Telecom

  • SpiderCloud Wireless

  • Symena

  • Tarana Wireless

  • Tektronix Communications

  • Telefónica

  • Tellabs

  • TEOCO

  • Teradata

  • Theta Networks

  • TI (Texas Instruments)

  • TIM Brasil

  • Trendium

  • TTG International

  • Tulinx

  • Ubiquisys

  • Vasona Networks

  • Viavi Solutions

  • WebRadar

  • Xceed Technologies

  • XCellAir

  • ZTE

The SON (Self-Organizing Networks) Ecosystem: 2015 – 2030 – Opportunities, Challenges, Strategies & Forecasts

Table of Contents

1 Chapter 1: Introduction 13
1.1 Executive Summary 13
1.2 Topics Covered 15
1.3 Historical Revenue & Forecast Segmentation 16
1.4 Key Questions Answered 18
1.5 Key Findings 19
1.6 Methodology 20
1.7 Target Audience 21
1.8 Companies & Organizations Mentioned 22

2 Chapter 2: SON & Mobile Network Optimization Ecosystem 25
2.1 Conventional Mobile Network Optimization 25
2.1.1 Network Planning 25
2.1.2 Measurement Collection: Drive Tests, Probes and End User Data 26
2.1.3 Post-Processing, Optimization & Policy Enforcement 26
2.2 The SON (Self-Organizing Network) Concept 27
2.2.1 What is SON? 27
2.2.2 The Need for SON 27
2.3 Functional Areas of SON 28
2.3.1 Self-Configuration 29
2.3.2 Self-Optimization 29
2.3.3 Self-Healing 29
2.4 Market Drivers for SON Adoption 30
2.4.1 Continued Wireless Network Infrastructure Investments 30
2.4.2 Optimization in Multi-RAN & HetNet Environments 32
2.4.3 OpEx & CapEx Reduction: The Cost Saving Potential 33
2.4.4 Improving Subscriber Experience and Churn Reduction 33
2.4.5 Power Savings 34
2.4.6 Enabling Small Cell Deployments 34
2.4.7 Traffic Management 34
2.5 Market Barriers for SON Adoption 34
2.5.1 Complexity of Implementation 35
2.5.2 Reorganization & Changes to Standard Engineering Procedures 35
2.5.3 Lack of Trust in Automation 35
2.5.4 Lack of Operator Control: Proprietary SON Algorithms 35
2.5.5 Coordination between Distributed and Centralized SON 36
2.5.6 Network Security Concerns: New Interfaces and Lack of Monitoring 36

3 Chapter 3: SON Technology, Use Cases & Implementation Architectures 37
3.1 Where Does SON Sit Within a Mobile Network? 37
3.1.1 RAN 38
3.1.2 Mobile Core 38
3.1.3 Mobile Backhaul & Transport 39
3.1.4 Device-Assisted SON 40
3.2 SON Architecture 41
3.2.1 C-SON (Centralized SON) 41
3.2.2 D-SON (Distributed SON) 42
3.2.3 H-SON (Hybrid SON) 43
3.3 SON Use-Cases 44
3.3.1 Self-Configuration of Network Elements 44
3.3.2 Automatic Connectivity Management 44
3.3.3 Self-Testing of Network Elements 44
3.3.4 Self-Recovery of Network Elements/Software 45
3.3.5 Self-Healing of Board Faults 45
3.3.6 Automatic Inventory 45
3.3.7 ANR (Automatic Neighbor Relations) 45
3.3.8 PCI (Physical Cell ID) Configuration 46
3.3.9 CCO (Coverage & Capacity Optimization) 46
3.3.10 MRO (Mobility Robustness Optimization) 46
3.3.11 MLB (Mobile Load Balancing) 47
3.3.12 RACH (Random Access Channel) Optimization 47
3.3.13 ICIC (Inter-Cell Interference Coordination) 47
3.3.14 eICIC (Enhanced ICIC) 48
3.3.15 Energy Savings 48
3.3.16 Cell Outage Detection & Compensation 48
3.3.17 Self-Configuration & Optimization of Small Cells 49
3.3.18 Optimization of DAS (Distributed Antenna Systems) 49
3.3.19 RAN Aware Traffic Shaping 49
3.3.20 Traffic Steering in HetNets 50
3.3.21 Optimization of Virtualized Network Resources 50
3.3.22 Auto-Provisioning of Transport Links 50
3.3.23 Transport Network Bandwidth Optimization 50
3.3.24 Transport Network Interference Management 50
3.3.25 SON Coordination Management 51
3.3.26 Seamless Vendor Infrastructure Swap 51

4 Chapter 4: SON Standardization 52
4.1 NGNM (Next Generation Mobile Networks) Alliance 52
4.1.1 Conception of the SON Initiative 52
4.1.2 Functional Areas and Requirements 53
4.1.3 Implementation Approach 54
4.1.4 P-SmallCell (Project Small Cell) 54
4.1.5 Recommendations for Multi-Vendor SON Deployment 55
4.2 3GPP (Third Generation Partnership Project) 56
4.2.1 Release 8 56
4.2.2 Release 9 57
4.2.3 Release 10 57
4.2.4 Release 11 57
4.2.5 Release 12, 13 & Beyond 58
4.2.6 Implementation Approach 59

5 Chapter 5: SON Deployment Case Studies 60
5.1 AT&T Mobility 60
5.1.1 Vendor Selection & Contract Value 60
5.1.2 Implemented Use Cases 60
5.1.3 Results 60
5.2 Singtel 61
5.2.1 Vendor Selection & Contract Value 61
5.2.2 Implemented Use Cases 61
5.2.3 Results 61
5.3 TIM Brasil 62
5.3.1 Vendor Selection & Contract Value 62
5.3.2 Implemented Use Cases 62
5.3.3 Results 62
5.4 KDDI 63
5.4.1 Vendor Selection & Contract Value 63
5.4.2 Implemented Use Cases 63
5.4.3 Results 63
5.5 SK Telecom 64
5.5.1 Vendor Selection & Contract Value 64
5.5.2 Implemented Use Cases 64
5.5.3 Results 64
5.6 Globe Telecom 65
5.6.1 Vendor Selection & Contract Value 65
5.6.2 Implemented Use Cases 65
5.6.3 Results 65

6 Chapter 6: Industry Roadmap & Value Chain 66
6.1 Industry Roadmap 66
6.1.1 Large Scale Adoption of SON Technology: 2015 - 2020 66
6.1.2 Towards QoE/QoS Based End-to-End SON: 2020 - 2025 67
6.1.3 Continued Investments to Support 5G Rollouts: 2025 - 2030 67
6.2 Value Chain 68
6.3 Embedded Technology Ecosystem 68
6.3.1 Chipset Developers 68
6.3.2 Embedded Component/Software Providers 68
6.4 RAN Ecosystem 70
6.4.1 Macrocell RAN OEMs 70
6.4.2 Pure-Play and Specialist Small Cell OEMs 70
6.4.3 WiFi Access Point OEMs 70
6.4.4 DAS & Repeater Solution Providers 70
6.4.5 C-RAN Solution Providers 71
6.4.6 Other Technology & Network Component Providers/Enablers 71
6.5 Mobile Backhaul & Fronthaul Ecosystem 71
6.5.1 Backhaul & Fronthaul Solution Providers 71
6.6 Mobile Core Ecosystem 71
6.6.1 Core Network Infrastructure & Software Providers 71
6.7 Connectivity Ecosystem 72
6.7.1 2G, 3G & 4G Wireless Carriers 72
6.7.2 WiFi Connectivity Providers 74
6.7.3 SCaaS (Small Cells as a Service) Providers 74
6.8 SON & Mobile Network Optimization Ecosystem 74
6.8.1 SON Solution Providers 74
6.8.2 Mobile Network Optimization Solution Providers 74
6.9 SDN & NFV Ecosystem 75
6.9.1 SDN & NFV Providers 75

7 Chapter 7: Vendor Landscape 76
7.1 Accedian Networks 76
7.2 Accuver 77
7.3 AirHop Communications 78
7.4 Airspan Networks 79
7.5 Alcatel-Lucent 80
7.6 Amdocs 81
7.7 Anite 82
7.8 Arcadyan 83
7.9 Argela 84
7.10 Aricent 85
7.11 ARItel 86
7.12 Ascom 87
7.13 Astellia 88
7.14 ATDI 89
7.15 Avago Technologies 90
7.16 Avvasi 91
7.17 BLiNQ Networks 92
7.18 Cavium 93
7.19 CBNL (Cambridge Broadband Networks Limited) 94
7.20 CellMining 95
7.21 Cellwize 96
7.22 Celtro Communications 97
7.23 CENTRI 98
7.24 Cisco Systems 99
7.25 Citrix Systems 100
7.26 Comarch 101
7.27 CommAgility 102
7.28 Commsquare 103
7.29 Coriant 104
7.30 Datang Mobile 105
7.31 ECE (European Communications Engineering) 106
7.32 Ericsson 107
7.33 Flash Networks 108
7.34 Forsk 109
7.35 Fujitsu 110
7.36 Guavus 111
7.37 Hitachi 112
7.38 Huawei 113
7.39 InfoVista 114
7.40 Intel Corporation 115
7.41 InterDigital 116
7.42 ip.access 117
7.43 Lavastorm 118
7.44 Lemko Corporation 119
7.45 NEC Corporation 120
7.46 Nokia Networks 121
7.47 NXP Semiconductors 122
7.48 Optulink 123
7.49 P.I.Works 124
7.50 Plano Engineering 125
7.51 Qualcomm 126
7.52 RADCOM 127
7.53 Radisys Corporation 128
7.54 Reverb Networks 129
7.55 Rohde & Schwarz 130
7.56 Rorotika 131
7.57 Samsung Electronics 132
7.58 SEDICOM 133
7.59 Siklu Communication 134
7.60 SpiderCloud Wireless 135
7.61 Tarana Wireless 136
7.62 Tektronix Communications 137
7.63 TEOCO 138
7.64 Theta Networks 139
7.65 TI (Texas Instruments) 140
7.66 TTG International 141
7.67 Tulinx 142
7.68 Vasona Networks 143
7.69 Viavi Solutions 144
7.70 WebRadar 145
7.71 XCellAir 146
7.72 ZTE 147

8 Chapter 8: Market Analysis & Forecasts 148
8.1 SON & Mobile Network Optimization Revenue 148
8.2 SON Revenue 149
8.3 SON Revenue by Network Segment 149
8.3.1 SON in RAN 150
8.3.2 SON in Mobile Core 150
8.3.3 SON in Mobile Backhaul 151
8.4 SON Revenue by Architecture: Centralized vs. Distributed 151
8.4.1 C-SON 152
8.4.2 D-SON 152
8.5 SON Revenue by Wireless Network Generation: 2G/3G vs. 4G & Beyond 153
8.5.1 2G & 3G SON 153
8.5.2 4G & Beyond SON 154
8.6 SON Revenue by Region 154
8.7 Conventional Mobile Network Planning & Optimization Revenue 155
8.8 Conventional Mobile Network Planning & Optimization Revenue by Region 155
8.9 Asia Pacific 156
8.9.1 SON 156
8.9.2 Conventional Mobile Network Planning & Optimization 156
8.10 Eastern Europe 157
8.10.1 SON 157
8.10.2 Conventional Mobile Network Planning & Optimization 157
8.11 Latin & Central America 158
8.11.1 SON 158
8.11.2 Conventional Mobile Network Planning & Optimization 158
8.12 Middle East & Africa 159
8.12.1 SON 159
8.12.2 Conventional Mobile Network Planning & Optimization 159
8.13 North America 160
8.13.1 SON 160
8.13.2 Conventional Mobile Network Planning & Optimization 160
8.14 Western Europe 161
8.14.1 SON 161
8.14.2 Conventional Mobile Network Planning & Optimization 161
8.15 Top Country Markets 162
8.15.1 Australia 162
8.15.2 Brazil 162
8.15.3 Canada 163
8.15.4 China 163
8.15.5 France 164
8.15.6 Germany 164
8.15.7 India 165
8.15.8 Italy 165
8.15.9 Japan 166
8.15.10 Russia 166
8.15.11 South Korea 167
8.15.12 Spain 167
8.15.13 Taiwan 168
8.15.14 UK 168
8.15.15 USA 169

9 Chapter 9: Conclusion & Strategic Recommendations 170
9.1 Moving Towards QoE Based SON Platforms 170
9.2 Capitalizing on DPI (Deep Packet Inspection) 170
9.3 The Convergence of Big Data, Predictive Analytics & SON 171
9.4 Optimizing M2M & IoT Services 172
9.5 SON for NFV & SDN: The Push from Mobile Operators 172
9.6 Moving Towards Mobile Core and Transport Networks 173
9.7 Assessing the Impact of SON on Optimization & Field Engineers 173
9.8 SON Associated OpEx Savings: The Numbers 175
9.9 What SON Capabilities Will 5G Networks Entail? 176
9.10 The C-SON Versus D-SON Debate 176
9.11 Strategic Recommendations 178
9.11.1 SON & Conventional Mobile Network Optimization Solution Providers 178
9.11.2 Wireless Infrastructure OEMs 179
9.11.3 Mobile Operators 180

List of Figures

Figure 1: Functional Areas of SON with the Mobile Network Lifecycle 28
Figure 2: Annual Global Throughput of Mobile Network Data Traffic by Region: 2015 – 2030 (Exabytes) 30
Figure 3: Global Wireless Network Infrastructure Revenue Share by Submarket (%) 31
Figure 4: Global Mobile Network Data Traffic Distribution by Access Network Form Factor: 2015 – 2030 (%) 32
Figure 5: SON Associated OpEx & CapEx Savings by Network Segment 33
Figure 6: Potential Areas of SON Implementation 37
Figure 7: Mobile Backhaul & Transport Segmentation by Technology 39
Figure 8: C-SON (Centralized SON) in a Wireless Carrier Network 41
Figure 9: D-SON (Distributed SON) in a Wireless Carrier Network 42
Figure 10: H-SON (Hybrid SON) in a Wireless Carrier Network 43
Figure 11: NGNM SON Use Cases 53
Figure 12: SON Industry Roadmap: 2015 - 2030 66
Figure 13: The Wireless Network Infrastructure Value Chain 69
Figure 14: List of LTE Trials & Deployments 73
Figure 15: Global SON & Mobile Network Optimization Revenue: 2015 - 2030 ($ Million) 148
Figure 16: Global SON Revenue: 2015 - 2030 ($ Million) 149
Figure 17: Global SON Revenue by Network Segment: 2015 - 2030 ($ Million) 149
Figure 18: Global RAN SON Revenue: 2015 - 2030 ($ Million) 150
Figure 19: Global Mobile Core SON Revenue: 2015 - 2030 ($ Million) 150
Figure 20: Global Mobile Backhaul & Transport SON Revenue: 2015 - 2030 ($ Million) 151
Figure 21: Global SON Revenue by Architecture: 2015 - 2030 ($ Million) 151
Figure 22: Global C-SON Revenue: 2015 - 2030 ($ Million) 152
Figure 23: Global D-SON Revenue: 2015 - 2030 ($ Million) 152
Figure 24: Global SON Revenue by Wireless Network Generation: 2015 - 2030 ($ Million) 153
Figure 25: Global 2G & 3G SON Revenue: 2015 - 2030 ($ Million) 153
Figure 26: Global 4G & Beyond SON Revenue: 2015 - 2030 ($ Million) 154
Figure 27: SON Revenue by Region: 2015 - 2030 ($ Million) 154
Figure 28: Global Conventional Mobile Network Planning & Optimization Revenue: 2015 - 2030 ($ Million) 155
Figure 29: Conventional Mobile Network Planning & Optimization Revenue by Region: 2015 - 2030 ($ Million) 155
Figure 30: Asia Pacific SON Revenue: 2015 - 2030 ($ Million) 156
Figure 31: Asia Pacific Conventional Mobile Network Planning & Optimization Revenue: 2015 - 2030 ($ Million) 156
Figure 32: Eastern Europe SON Revenue: 2015 - 2030 ($ Million) 157
Figure 33: Eastern Europe Conventional Mobile Network Planning & Optimization Revenue: 2015 - 2030 ($ Million) 157
Figure 34: Latin & Central America SON Revenue: 2015 - 2030 ($ Million) 158
Figure 35: Latin & Central America Conventional Mobile Network Planning & Optimization Revenue: 2015 - 2030 ($ Million) 158
Figure 36: Middle East & Africa SON Revenue: 2015 - 2030 ($ Million) 159
Figure 37: Middle East & Africa Conventional Mobile Network Planning & Optimization Revenue: 2015 - 2030 ($ Million) 159
Figure 38: North America SON Revenue: 2015 - 2030 ($ Million) 160
Figure 39: North America Conventional Mobile Network Planning & Optimization Revenue: 2015 - 2030 ($ Million) 160
Figure 40: Western Europe SON Revenue: 2015 - 2030 ($ Million) 161
Figure 41: Western Europe Conventional Mobile Network Planning & Optimization Revenue: 2015 - 2030 ($ Million) 161
Figure 42: Australia SON Revenue: 2015 - 2030 ($ Million) 162
Figure 43: Brazil SON Revenue: 2015 - 2030 ($ Million) 162
Figure 44: Canada SON Revenue: 2015 - 2030 ($ Million) 163
Figure 45: China SON Revenue: 2015 - 2030 ($ Million) 163
Figure 46: France SON Revenue: 2015 - 2030 ($ Million) 164
Figure 47: Germany SON Revenue: 2015 - 2030 ($ Million) 164
Figure 48: India SON Revenue: 2015 - 2030 ($ Million) 165
Figure 49: Italy SON Revenue: 2015 - 2030 ($ Million) 165
Figure 50: Japan SON Revenue: 2015 - 2030 ($ Million) 166
Figure 51: Russia SON Revenue: 2015 - 2030 ($ Million) 166
Figure 52: South Korea SON Revenue: 2015 - 2030 ($ Million) 167
Figure 53: Spain SON Revenue: 2015 - 2030 ($ Million) 167
Figure 54: Taiwan SON Revenue: 2015 - 2030 ($ Million) 168
Figure 55: UK SON Revenue: 2015 - 2030 ($ Million) 168
Figure 56: USA SON Revenue: 2015 - 2030 ($ Million) 169
Figure 57: SON Associated OpEx Savings by Region: 2015 - 2030 ($ Million) 175

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