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Published: Sep, 2018 | Pages:
367 | Publisher: SNS Research
Industry: Telecommunications | Report Format: Electronic (PDF)
SON (Self-Organizing Network) technology minimizes the lifecycle cost of running a mobile network by eliminating manual configuration of network elements at the time of deployment, right through to dynamic optimization and troubleshooting during operation. Besides improving network performance and customer experience, SON can significantly reduce the cost of mobile operator services, improving the OpEx-to-revenue ratio and deferring avoidable CapEx. To support their LTE and HetNet deployments, early adopters of SON have already witnessed a spate of benefits - in the form of accelerated rollout times, simplified network upgrades, fewer dropped calls, improved call setup success rates, higher end-user throughput, alleviation of congestion during special events, increased subscriber satisfaction and loyalty, and operational efficiencies - such as energy and cost savings, and freeing up radio engineers from repetitive manual tasks. Although SON was originally developed as an operational approach to streamline cellular RAN (Radio Access Network) deployment and optimization, mobile operators and vendors are increasingly focusing on integrating new capabilities such as self-protection against digital security threats, and self-learning through artificial intelligence techniques, as well as extending the scope of SON beyond the RAN to include both mobile core and transport network segments - which will be critical to address 5G requirements such as end-to-end network slicing. In addition, dedicated SON solutions for Wi-Fi and other access technologies have also emerged, to simplify wireless networking in home and enterprise environments. Largely driven by the increasing complexity of today's multi-RAN mobile networks - including network densification and spectrum heterogeneity, as well as 5G NR (New Radio) infrastructure rollouts, global investments in SON technology are expected to grow at a CAGR of approximately 11% between 2019 and 2022. By the end of 2022, SNS Telecom & IT estimates that SON will account for a market worth $5.5 Billion. The “SON (Self-Organizing Networks) in the 5G Era: 2019 - 2030 - Opportunities, Challenges, Strategies & Forecasts” report presents an in-depth assessment of the SON and associated mobile network optimization ecosystem, including market drivers, challenges, enabling technologies, functional areas, use cases, key trends, standardization, regulatory landscape, mobile operator case studies, opportunities, future roadmap, value chain, ecosystem player profiles and strategies. The report also presents revenue forecasts for both SON and conventional mobile network optimization, along with individual projections for 10 SON submarkets, and 6 regions from 2019 till 2030. The report comes with an associated Excel datasheet suite covering quantitative data from all numeric forecasts presented in the report. Topics Covered The report covers the following topics: - SON ecosystem - Market drivers and barriers - Conventional mobile network planning & optimization - Mobile network infrastructure spending, traffic projections and value chain - SON technology, architecture & functional areas - Review of over 30 SON use cases - ranging from automated neighbor relations and parameter optimization to self-protection and cognitive networks - Case studies of 15 commercial SON deployments by mobile operators - Complementary technologies including Big Data, advanced analytics, artificial intelligence and machine learning - Key trends in next-generation LTE and 5G SON implementations including network slicing, dynamic spectrum management, edge computing, virtualization and zero-touch automation - Regulatory landscape, collaborative initiatives and standardization - SON future roadmap: 2019 - 2030 - Profiles and strategies of more than 160 leading ecosystem players including wireless network infrastructure OEMs, SON solution providers and mobile operators - Strategic recommendations for SON solution providers and mobile operators - Market analysis and forecasts from 2019 till 2030 Forecast Segmentation Market forecasts 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 (Radio Access Network) - Mobile Core - Transport (Backhaul & Fronthaul) SON Architecture Submarkets - C-SON (Centralized SON) - D-SON (Distributed SON) - SON Access Network Technology Submarkets - 2G & 3G - LTE - 5G - Wi-Fi & Others Regional Markets - Asia Pacific - Eastern Europe - Latin & Central America - Middle East & Africa - North America - Western Europe Key Questions Answered The report provides answers to the following key questions: - How big is the SON opportunity? - What trends, challenges and barriers are influencing its growth? - How is the ecosystem evolving by segment and region? - What will the market size be in 2022, and at what rate will it grow? - Which regions and countries will see the highest percentage of growth? - How do SON investments compare with spending on traditional mobile network optimization? - What are the practical, quantifiable benefits of SON - based on live, commercial deployments? - How can mobile operators capitalize on SON to ensure optimal network performance, improve customer experience, reduce costs, and drive revenue growth? - What is the status of C-SON and D-SON adoption worldwide? - What are the prospects of artificial intelligence in SON and mobile network automation? - What opportunities exist for SON in mobile core and transport networks? - How can SON ease the deployment of unlicensed and private LTE/5G-ready networks? - What SON capabilities will 5G networks entail? - How does SON impact mobile network optimization engineers? - What is the global and regional outlook for SON associated OpEx savings? - Who are the key ecosystem players, and what are their strategies? - What strategies should SON solution providers and mobile operators adopt to remain competitive? Key Findings The report has the following key findings: - Largely driven by the increasing complexity of today's multi-RAN mobile networks - including network densification and spectrum heterogeneity, as well as 5G NR (New Radio) infrastructure rollouts, global investments in SON technology are expected to grow at a CAGR of approximately 11% between 2019 and 2022. By the end of 2022, SNS Telecom & IT estimates that SON will account for a market worth $5.5 Billion. - Based on feedback from mobile operators worldwide, the growing adoption of SON technology has brought about a host of practical benefits for early adopters - ranging from more than a 50% decline in dropped calls and reduction in network congestion during special events by a staggering 80% to OpEx savings of more than 30% and an increase in service revenue by 5-10%. - In addition, SON mechanisms are playing a pivotal role in accelerating the adoption of 5G networks - through the enablement of advanced capabilities such as network slicing, dynamic spectrum management, predictive resource allocation, and the automated of deployment of virtualized 5G network functions. - To better address network performance challenges amidst increasing complexity, C-SON platforms are leveraging an array of complementary technologies - from artificial intelligence and machine learning algorithms to Big Data technologies and the use of alternative data such as information extracted from crowd-sourcing tools. - In addition to infrastructure vendor and third-party offerings, mobile operator developed SON solutions are also beginning to emerge. For example, Elisa has developed a SON platform based on closed-loop automation and customizable algorithms for dynamic network optimization. Through a dedicated business unit, the Finnish operator offers its in-house SON implementation as a commercial product to other mobile operators. List of Companies Mentioned • 3GPP (Third Generation Partnership Project) • 5G PPP (5G Infrastructure Public Private Partnership) • Accedian Networks • Accelleran • Accuver • Actix • AIRCOM International • AirHop Communications • Airspan Networks • Allot Communications • Alpha Networks • Alphabet • Altiostar Networks • Altran • Alvarion Technologies • Amdocs • Anritsu Corporation • Arcadyan Technology Corporation • Argela • ARIB (Association of Radio Industries and Businesses, Japan) • Aricent • Arista Networks • ARRIS International • Artemis Networks • Artiza Networks • ASOCS • Astellia • ASUS (ASUSTeK Computer) • AT&T • ATDI • ATIS (Alliance for Telecommunications Industry Solutions, United States) • Baicells Technologies • BCE (Bell Canada) • Benu Networks • Bharti Airtel • BLiNQ Networks • BoostEdge • Broadcom • CableLabs • Casa Systems • Cavium • CBNL (Cambridge Broadband Networks Limited) • CCI (Communication Components, Inc.) • CCS (Cambridge Communication Systems) • CCSA (China Communications Standards Association) • Celcite • CellOnyx • Cellwize • CelPlan Technologies • Celtro • Cisco Systems • Citrix Systems • Collision Communications • Comarch • CommAgility • CommProve • CommScope • Commsquare • Comsearch • Contela • Continual • Coriant • Corning • Datang Mobile • Dell Technologies • Digi Communications • Digitata • D-Link Corporation • ECE (European Communications Engineering) • EDX Wireless • Elisa • Elisa Automate • Empirix • Equiendo • Ercom • Ericsson • ETRI (Electronics & Telecommunications Research Institute, South Korea) • ETSI (European Telecommunications Standards Institute) • EXFO • Facebook • Fairspectrum • Federated Wireless • Flash Networks • Fon • Fontech • Forsk • Fujian Sunnada Network Technology • Fujitsu • Galgus • Gemtek Technology • General Dynamics Mission Systems • GenXComm • Globe Telecom • GoNet Systems • Google • Guavus • GWT (Global Wireless Technologies) • HCL Technologies • Hitachi • Hitachi Vantara • Huawei • iBwave Solutions • InfoVista • Innovile • InnoWireless • Intel Corporation • InterDigital • Intracom Telecom • ip.access • ITRI (Industrial Technology Research Institute, Taiwan) • Ixia • JRC (Japan Radio Company) • Juni Global • Juniper Networks • KDDI Corporation • Keima • Key Bridge • Keysight Technologies • KKTCell (Kuzey Kıbrıs Turkcell) • Kleos • Koonsys Radiocommunications • Kumu Networks • Lemko Corporation • life:) Belarus • lifecell Ukraine • Linksys • Linux Foundation • LS telcom • Luminate Wireless • LuxCarta • Marvell Technology Group • Mavenir Systems • MegaFon • Mimosa Networks • MitraStar Technology Corporation • Mojo Networks • Mosaik • Nash Technologies • NEC Corporation • NetQPro • NetScout Systems • Netsia • New Postcom Equipment Company • Nexus Telecom • NGMN Alliance • Node-H • Nokia Networks • Nomor Research • NuRAN Wireless • Nutaq Innovation • NXP Semiconductors • Oceus Networks • Optus • Orange • P.I.Works • Parallel Wireless • Persistent Systems • PHAZR • Phluido • Polystar • Potevio • PreClarity • Qualcomm • Quanta Computer • Qucell • RADCOM • Radisys Corporation • Ranplan Wireless Network Design • RCS & RDS • Rearden • Red Hat • RED Technologies • Redline Communications • Reliance Industries • Rivada Networks • Rohde & Schwarz • Ruckus Wireless • Saguna Networks • Samji Electronics Company • Samsung • Schema • SEDICOM • SerComm Corporation • Seven Networks • Siklu Communication • Singtel • SIRADEL • SITRONICS • SK Telecom • SK Telesys • Small Cell Forum • Spectrum Effect • SpiderCloud Wireless • Star Solutions • SuperCom • Systemics Group • Tarana Wireless • Tech Mahindra • Tecore Networks • TEKTELIC Communications • Telefónica Group • Telrad Networks • TEOCO Corporation • Teragence • Thales • TI (Texas Instruments) • TIM (Telecom Italia Mobile) • TIM Brasil • TP-Link Technologies • TSDSI (Telecommunications Standards Development Society, India) • TTA (Telecommunications Technology Association, South Korea) • TTC (Telecommunication Technology Committee, Japan) • TTG International • Tulinx • Turkcell • Vasona Networks • Verizon Communications • VHA (Vodafone Hutchison Australia) • Viavi Solutions • VMWare • Vodafone Germany • Vodafone Group • Vodafone Ireland • Vodafone Spain • Vodafone UK • WBA (Wireless Broadband Alliance) • WebRadar • Wireless DNA • WNC (Wistron NeWeb Corporation) • WPOTECH • XCellAir • Z-Com • ZTE • Zyxel Communications Corporation
Table of Contents 1 Chapter 1: Introduction 19 1.1 Executive Summary 19 1.2 Topics Covered 21 1.3 Forecast Segmentation 22 1.4 Key Questions Answered 23 1.5 Key Findings 24 1.6 Methodology 26 1.7 Target Audience 27 1.8 Companies & Organizations Mentioned 28 2 Chapter 2: SON & Mobile Network Optimization Ecosystem 31 2.1 Conventional Mobile Network Optimization 31 2.1.1 Network Planning 31 2.1.2 Measurement Collection: Drive Tests, Probes and End User Data 32 2.1.3 Post-Processing, Optimization & Policy Enforcement 32 2.2 The SON (Self-Organizing Network) Concept 33 2.2.1 What is SON? 33 2.2.2 The Need for SON 33 2.3 Functional Areas of SON 34 2.3.1 Self-Configuration 35 2.3.2 Self-Optimization 35 2.3.3 Self-Healing 35 2.3.4 Self-Protection 36 2.3.5 Self-Learning 36 2.4 Market Drivers for SON Adoption 37 2.4.1 The 5G Era: Continued Mobile Network Infrastructure Investments 37 2.4.2 Optimization in Multi-RAN & HetNet Environments 39 2.4.3 OpEx & CapEx Reduction: The Cost Savings Potential 39 2.4.4 Improving Subscriber Experience and Churn Reduction 40 2.4.5 Power Savings: Towards Green Mobile Networks 40 2.4.6 Alleviating Congestion with Traffic Management 41 2.4.7 Enabling Large-Scale Small Cell Rollouts 41 2.4.8 Growing Adoption of Private LTE & 5G-Ready Networks 41 2.5 Market Barriers for SON Adoption 42 2.5.1 Complexity of Implementation 42 2.5.2 Reorganization & Changes to Standard Engineering Procedures 42 2.5.3 Lack of Trust in Automation 42 2.5.4 Proprietary SON Algorithms 42 2.5.5 Coordination Between Distributed and Centralized SON 43 2.5.6 Network Security Concerns: New Interfaces and Lack of Monitoring 43 3 Chapter 3: SON Technology, Use Cases & Implementation Architectures 44 3.1 Where Does SON Sit Within a Mobile Network? 44 3.1.1 RAN 45 3.1.2 Mobile Core 45 3.1.3 Transport (Backhaul & Fronthaul) 46 3.1.4 Device-Assisted SON 47 3.2 SON Architecture 48 3.2.1 C-SON (Centralized SON) 48 3.2.2 D-SON (Distributed SON) 49 3.2.3 H-SON (Hybrid SON) 50 3.3 SON Use-Cases 51 3.3.1 Self-Configuration of Network Elements 51 3.3.2 Automatic Connectivity Management 51 3.3.3 Self-Testing of Network Elements 51 3.3.4 Self-Recovery of Network Elements/Software 51 3.3.5 Self-Healing of Board Faults 52 3.3.6 Automatic Inventory 52 3.3.7 ANR (Automatic Neighbor Relations) 52 3.3.8 PCI (Physical Cell ID) Configuration 52 3.3.9 CCO (Coverage & Capacity Optimization) 53 3.3.10 MRO (Mobility Robustness Optimization) 53 3.3.11 MLB (Mobility Load Balancing) 53 3.3.12 RACH (Random Access Channel) Optimization 54 3.3.13 ICIC (Inter-Cell Interference Coordination) 54 3.3.14 eICIC (Enhanced ICIC) 55 3.3.15 Energy Savings 55 3.3.16 COD/COC (Cell Outage Detection & Compensation) 55 3.3.17 MDT (Minimization of Drive Tests) 56 3.3.18 AAS (Adaptive Antenna Systems) & Massive MIMO 56 3.3.19 Millimeter Wave Links in 5G NR (New Radio) Networks 56 3.3.20 Self-Configuration & Optimization of Small Cells 56 3.3.21 Optimization of DAS (Distributed Antenna Systems) 57 3.3.22 RAN Aware Traffic Shaping 57 3.3.23 Traffic Steering in HetNets 57 3.3.24 Optimization of NFV-Based Networking 57 3.3.25 Auto-Provisioning of Transport Links 58 3.3.26 Transport Network Bandwidth Optimization 58 3.3.27 Transport Network Interference Management 58 3.3.28 Self-Protection 59 3.3.29 SON Coordination Management 59 3.3.30 Seamless Vendor Infrastructure Swap 59 3.3.31 Dynamic Spectrum Management & Allocation 59 3.3.32 Network Slice Optimization 59 3.3.33 Cognitive & Self-Learning Networks 60 4 Chapter 4: Key Trends in Next-Generation LTE & 5G SON Implementations 61 4.1 Big Data & Advanced Analytics 61 4.1.1 Maximizing the Benefits of SON with Big Data 61 4.1.2 The Importance of Predictive & Behavioral Analytics 62 4.2 Artificial Intelligence & Machine Learning 62 4.2.1 Towards Self-Learning SON Engines with Machine Learning 63 4.2.2 Deep Learning: Enabling "Zero-Touch" Mobile Networks 63 4.3 NFV (Network Functions Virtualization) 64 4.3.1 Enabling the SON-Driven Deployment of VNFs (Virtualized Network Functions) 65 4.4 SDN (Software Defined Networking) & Programmability 66 4.4.1 Using the SDN Controller as a Platform for SON in Transport Networks 66 4.5 Cloud Computing 67 4.5.1 Facilitating C-SON Scalability & Elasticity 67 4.6 Small Cells, HetNets & RAN Densification 67 4.6.1 Plug & Play Small Cells 68 4.6.2 Coordinating UDNs (Ultra Dense Networks) with SON 68 4.7 C-RAN (Centralized RAN) & Cloud RAN 69 4.7.1 Efficient Resource Utilization in C-RAN Deployments with SON 70 4.8 Unlicensed & Shared Spectrum Usage 71 4.8.1 Dynamic Management of Spectrum with SON 72 4.9 MEC (Multi-Access Edge Computing) 72 4.9.1 Potential Synergies with SON 73 4.10 Network Slicing 73 4.10.1 Use of SON Mechanisms for Network Slicing in 5G Networks 74 4.11 Other Trends & Complementary Technologies 75 4.11.1 Alternative Carrier/Private LTE & 5G-Ready Networks 75 4.11.2 FWA (Fixed Wireless Access) 76 4.11.3 DPI (Deep Packet Inspection) 76 4.11.4 Digital Security for Self-Protection 77 4.11.5 SON Capabilities for IoT Applications 78 4.11.6 User-Based Profiling & Optimization for Vertical 5G Applications 78 4.11.7 Addressing D2D (Device-to-Device) Communications & New Use Cases 79 5 Chapter 5: Standardization, Regulatory & Collaborative Initiatives 80 5.1 3GPP (Third Generation Partnership Project) 80 5.1.1 Standardization of SON Capabilities for 3GPP Networks 80 5.1.2 Release 8 81 5.1.3 Release 9 81 5.1.4 Release 10 81 5.1.5 Release 11 82 5.1.6 Release 12 83 5.1.7 Releases 13 & 14 83 5.1.8 Releases 15, 16 & Beyond 83 5.1.9 Implementation Approach for 3GPP-Specified SON Features 84 5.2 NGMN Alliance 84 5.2.1 Conception of the SON Initiative 84 5.2.2 Functional Areas and Requirements 85 5.2.3 Implementation Approach: Focus on H-SON 86 5.2.4 Recommendations for Multi-Vendor SON Deployment 86 5.2.5 SON Capabilities for 5G Network Deployment, Operation & Management 87 5.3 ETSI (European Telecommunications Standards Institute) 87 5.3.1 ENI ISG (Experiential Networked Intelligence Industry Specification Group) 88 5.4 Linux Foundation's ONAP (Open Network Automation Platform) 88 5.4.1 ONAP Support for SON in 5G Networks 89 5.5 OSSii (Operations Support Systems Interoperability Initiative) 89 5.5.1 Enabling Multi-Vendor SON Interoperability 89 5.6 Small Cell Forum 90 5.6.1 Release 7: Focus on SON for Small Cells 90 5.6.2 SON API 90 5.6.3 X2 Interoperability 91 5.7 WBA (Wireless Broadband Alliance) 91 5.7.1 SON Integration in Carrier Wi-Fi Guidelines 91 5.8 CableLabs 92 5.8.1 Wi-Fi RRM (Radio Resource Management)/SON 92 5.9 5G PPP (5G Infrastructure Public Private Partnership) & European Union Projects 92 5.9.1 SELFNET (Framework for Self-Organized Network Management in Virtualized and Software Defined Networks) 93 5.9.2 SEMAFOUR (Self-Management for Unified Heterogeneous Radio Access Networks) 94 5.9.3 SOCRATES (Self-Optimization and Self-Configuration in Wireless Networks) 94 5.9.4 COGNET (Building an Intelligent System of Insights and Action for 5G Network Management) 95 6 Chapter 6: SON Deployment Case Studies 96 6.1 AT&T 96 6.1.1 Vendor Selection 96 6.1.2 SON Deployment Review 96 6.1.3 Results & Future Plans 98 6.2 BCE (Bell Canada) 99 6.2.1 Vendor Selection 99 6.2.2 SON Deployment Review 99 6.2.3 Results & Future Plans 100 6.3 Bharti Airtel 101 6.3.1 Vendor Selection 101 6.3.2 SON Deployment Review 101 6.3.3 Results & Future Plans 102 6.4 Elisa 103 6.4.1 Vendor Selection 103 6.4.2 SON Deployment Review 103 6.4.3 Results & Future Plans 105 6.5 Globe Telecom 106 6.5.1 Vendor Selection 106 6.5.2 SON Deployment Review 106 6.5.3 Results & Future Plans 107 6.6 KDDI Corporation 108 6.6.1 Vendor Selection 108 6.6.2 SON Deployment Review 108 6.6.3 Results & Future Plans 109 6.7 MegaFon 111 6.7.1 Vendor Selection 111 6.7.2 SON Deployment Review 111 6.7.3 Results & Future Plans 112 6.8 Orange 114 6.8.1 Vendor Selection 114 6.8.2 SON Deployment Review 114 6.8.3 Results & Future Plans 115 6.9 Singtel 117 6.9.1 Vendor Selection 117 6.9.2 SON Deployment Review 117 6.9.3 Results & Future Plans 118 6.10 SK Telecom 119 6.10.1 Vendor Selection 119 6.10.2 SON Deployment Review 120 6.10.3 Results & Future Plans 122 6.11 Telefónica Group 123 6.11.1 Vendor Selection 123 6.11.2 SON Deployment Review 123 6.11.3 Results & Future Plans 124 6.12 TIM (Telecom Italia Mobile) 126 6.12.1 Vendor Selection 126 6.12.2 SON Deployment Review 126 6.12.3 Results & Future Plans 128 6.13 Turkcell 129 6.13.1 Vendor Selection 129 6.13.2 SON Deployment Review 129 6.13.3 Results & Future Plans 130 6.14 Verizon Communications 131 6.14.1 Vendor Selection 131 6.14.2 SON Deployment Review 131 6.14.3 Results & Future Plans 132 6.15 Vodafone Group 133 6.15.1 Vendor Selection 133 6.15.2 SON Deployment Review 133 6.15.3 Results & Future Plans 134 7 Chapter 7: Future Roadmap & Value Chain 136 7.1 Future Roadmap 136 7.1.1 Pre-2020: Addressing Customer QoE, Network Densification & Early 5G Rollouts 136 7.1.2 2020 - 2025: Towards Advanced Machine Learning Based SON Implementations 137 7.1.3 2025 - 2030: Enabling Near Zero-Touch & Automated 5G Networks 137 7.2 Value Chain 138 7.3 Embedded Technology Ecosystem 138 7.3.1 Chipset Developers 138 7.3.2 Embedded Component/Software Providers 138 7.4 RAN Ecosystem 140 7.4.1 Macrocell RAN OEMs 140 7.4.2 Pure-Play Small Cell OEMs 140 7.4.3 Wi-Fi Access Point OEMs 140 7.4.4 DAS & Repeater Solution Providers 141 7.4.5 C-RAN Solution Providers 141 7.4.6 Other Technology Providers 141 7.5 Transport Networking Ecosystem 141 7.5.1 Backhaul & Fronthaul Solution Providers 141 7.6 Mobile Core Ecosystem 142 7.6.1 Mobile Core Solution Providers 142 7.7 Connectivity Ecosystem 142 7.7.1 Mobile Operators 142 7.7.2 Wi-Fi Connectivity Providers 142 7.7.3 SCaaS (Small-Cells-as-a-Service) Providers 143 7.8 SON Ecosystem 143 7.8.1 SON Solution Providers 143 7.9 SDN & NFV Ecosystem 143 7.9.1 SDN & NFV Providers 143 7.10 MEC Ecosystem 144 7.10.1 MEC Specialists 144 8 Chapter 8: Key Ecosystem Players 145 8.1 Accedian Networks 145 8.2 Accelleran 146 8.3 AirHop Communications 147 8.4 Airspan Networks 148 8.5 Allot Communications 150 8.6 Alpha Networks 151 8.7 Altiostar Networks 152 8.8 Altran/Aricent 153 8.9 Alvarion Technologies/SuperCom 154 8.10 Amdocs 155 8.11 Anritsu Corporation 157 8.12 Arcadyan Technology Corporation 158 8.13 Argela/Netsia 159 8.14 Artemis Networks 161 8.15 Artiza Networks 162 8.16 ASOCS 163 8.17 ASUS (ASUSTeK Computer) 164 8.18 ATDI 165 8.19 Baicells Technologies 166 8.20 Benu Networks 167 8.21 BoostEdge 168 8.22 Broadcom 169 8.23 Casa Systems 170 8.24 CBNL (Cambridge Broadband Networks Limited) 171 8.25 CCI (Communication Components, Inc.)/BLiNQ Networks 172 8.26 CCS (Cambridge Communication Systems) 173 8.27 CellOnyx 174 8.28 Cellwize 175 8.29 CelPlan Technologies 178 8.30 Celtro 179 8.31 Cisco Systems 180 8.32 Citrix Systems 182 8.33 Collision Communications 183 8.34 Comarch 184 8.35 CommAgility 186 8.36 CommScope 187 8.37 CommProve 189 8.38 Contela 190 8.39 Continual 191 8.40 Coriant 193 8.41 Corning/SpiderCloud Wireless 194 8.42 Datang Mobile 196 8.43 Dell Technologies 197 8.44 Digitata 198 8.45 D-Link Corporation 199 8.46 ECE (European Communications Engineering) 200 8.47 EDX Wireless 201 8.48 Elisa Automate 202 8.49 Empirix 203 8.50 Equiendo 204 8.51 Ercom 205 8.52 Ericsson 206 8.53 ETRI (Electronics & Telecommunications Research Institute, South Korea) 208 8.54 EXFO/Astellia 209 8.55 Facebook 211 8.56 Fairspectrum 212 8.57 Federated Wireless 213 8.58 Flash Networks 214 8.59 Forsk 216 8.60 Fujian Sunnada Network Technology 217 8.61 Fujitsu 218 8.62 Galgus 219 8.63 Gemtek Technology 220 8.64 General Dynamics Mission Systems 221 8.65 GenXComm 222 8.66 GoNet Systems 223 8.67 Google/Alphabet 224 8.68 Guavus/Thales 225 8.69 GWT (Global Wireless Technologies) 226 8.70 HCL Technologies 227 8.71 Hitachi 228 8.72 Huawei 230 8.73 iBwave Solutions 232 8.74 InfoVista 233 8.75 Innovile 234 8.76 InnoWireless/Qucell/Accuver 235 8.77 Intel Corporation 237 8.78 InterDigital 238 8.79 Intracom Telecom 239 8.80 ip.access 240 8.81 ITRI (Industrial Technology Research Institute, Taiwan) 241 8.82 JRC (Japan Radio Company) 242 8.83 Juni Global 243 8.84 Juniper Networks 244 8.85 Keima 245 8.86 Key Bridge 246 8.87 Keysight Technologies/Ixia 247 8.88 Kleos 249 8.89 Koonsys Radiocommunications 250 8.90 Kumu Networks 251 8.91 Lemko Corporation 252 8.92 Linksys 253 8.93 LS telcom 254 8.94 Luminate Wireless 255 8.95 LuxCarta 256 8.96 Marvell Technology Group/Cavium 257 8.97 Mavenir Systems 258 8.98 Mimosa Networks 260 8.99 MitraStar Technology Corporation 261 8.100 Mojo Networks/Arista Networks 262 8.101 Mosaik 263 8.102 Nash Technologies 264 8.103 NEC Corporation 265 8.104 NetScout Systems 267 8.105 New Postcom Equipment Company 269 8.106 Node-H 270 8.107 Nokia Networks 271 8.108 Nomor Research 273 8.109 NuRAN Wireless/Nutaq Innovation 274 8.110 NXP Semiconductors 275 8.111 Oceus Networks 276 8.112 P.I.Works 277 8.113 Parallel Wireless 278 8.114 Persistent Systems 279 8.115 PHAZR 280 8.116 Phluido 281 8.117 Polystar 282 8.118 Potevio 283 8.119 Qualcomm 284 8.120 Quanta Computer 286 8.121 RADCOM 287 8.122 Radisys Corporation/Reliance Industries 288 8.123 Ranplan Wireless Network Design 290 8.124 RED Technologies 291 8.125 Redline Communications 293 8.126 Rivada Networks 294 8.127 Rohde & Schwarz 295 8.128 Ruckus Wireless/ARRIS International 296 8.129 Saguna Networks 297 8.130 Samji Electronics Company 298 8.131 Samsung 299 8.132 SEDICOM 301 8.133 SerComm Corporation 302 8.134 Seven Networks 303 8.135 Siklu Communication 305 8.136 SIRADEL 306 8.137 SITRONICS 307 8.138 SK Telesys 308 8.139 Spectrum Effect 309 8.140 Star Solutions 310 8.141 Systemics Group 311 8.142 Tarana Wireless 312 8.143 Tech Mahindra 313 8.144 Tecore Networks 314 8.145 TEKTELIC Communications 315 8.146 Telrad Networks 316 8.147 TEOCO Corporation 317 8.148 Teragence 319 8.149 TI (Texas Instruments) 320 8.150 TP-Link Technologies 321 8.151 TTG International 322 8.152 Tulinx 323 8.153 Vasona Networks 324 8.154 Viavi Solutions 325 8.155 VMWare 327 8.156 WebRadar 328 8.157 Wireless DNA 329 8.158 WNC (Wistron NeWeb Corporation) 330 8.159 WPOTECH 331 8.160 XCellAir/Fontech 332 8.161 Z-Com 333 8.162 ZTE 334 8.163 Zyxel Communications Corporation 335 9 Chapter 9: Market Sizing & Forecasts 336 9.1 SON & Mobile Network Optimization Revenue 336 9.2 SON Revenue 337 9.3 SON Revenue by Network Segment 337 9.3.1 RAN 338 9.3.2 Mobile Core 338 9.3.3 Transport (Backhaul & Fronthaul) 339 9.4 SON Revenue by Architecture: Centralized vs. Distributed 339 9.4.1 C-SON 340 9.4.2 D-SON 340 9.5 SON Revenue by Access Network Technology 341 9.5.1 2G & 3G 341 9.5.2 LTE 342 9.5.3 5G 342 9.5.4 Wi-Fi 343 9.6 SON Revenue by Region 343 9.7 Conventional Mobile Network Planning & Optimization Revenue 344 9.8 Conventional Mobile Network Planning & Optimization Revenue by Region 344 9.9 Asia Pacific 345 9.9.1 SON 345 9.9.2 Conventional Mobile Network Planning & Optimization 345 9.10 Eastern Europe 346 9.10.1 SON 346 9.10.2 Conventional Mobile Network Planning & Optimization 346 9.11 Latin & Central America 347 9.11.1 SON 347 9.11.2 Conventional Mobile Network Planning & Optimization 347 9.12 Middle East & Africa 348 9.12.1 SON 348 9.12.2 Conventional Mobile Network Planning & Optimization 348 9.13 North America 349 9.13.1 SON 349 9.13.2 Conventional Mobile Network Planning & Optimization 349 9.14 Western Europe 350 9.14.1 SON 350 9.14.2 Conventional Mobile Network Planning & Optimization 350 10 Chapter 10: Conclusion & Strategic Recommendations 351 10.1 Why is the Market Poised to Grow? 351 10.2 Competitive Industry Landscape: Acquisitions, Alliances & Consolidation 352 10.3 Evaluating the Practical Benefits of SON 352 10.4 End-to-End SON: Moving Towards Mobile Core and Transport Networks 353 10.5 Growing Adoption of SON Capabilities for Wi-Fi 354 10.6 The Importance of Artificial Intelligence & Machine Learning 355 10.7 QoE-Based SON Platforms: Optimizing End User Experience 357 10.8 Enabling Network Slicing & Advanced Capabilities for 5G Networks 357 10.9 Greater Focus on Self-Protection Capabilities 359 10.10 Addressing IoT Optimization 359 10.11 Managing Unlicensed & Shared Spectrum 360 10.12 Easing the Deployment of Private & Enterprise LTE/5G-Ready Networks 361 10.13 Assessing the Impact of SON on Optimization & Field Engineers 362 10.14 SON Associated OpEx Savings: The Numbers 363 10.15 The C-SON Versus D-SON Debate 364 10.16 Strategic Recommendations 365 10.16.1 SON Solution Providers 365 10.16.2 Mobile Operators 366
List of Figures Figure 1: Functional Areas of SON within the Mobile Network Lifecycle 34 Figure 2: Annual Throughput of Mobile Network Data Traffic by Region: 2019 - 2030 (Exabytes) 37 Figure 3: Global Wireless Network Infrastructure Revenue Share by Submarket (%) 38 Figure 4: SON Associated OpEx & CapEx Savings by Network Segment (%) 40 Figure 5: Potential Areas of SON Implementation 44 Figure 6: Mobile Backhaul & Fronthaul Technologies 46 Figure 7: C-SON (Centralized SON) in a Mobile Operator Network 48 Figure 8: D-SON (Distributed SON) in a Mobile Operator Network 49 Figure 9: H-SON (Hybrid SON) in a Mobile Operator Network 50 Figure 10: NFV Concept 65 Figure 11: Transition to UDNs (Ultra-Dense Networks) 68 Figure 12: C-RAN Architecture 69 Figure 13: Conceptual Architecture for End-to-End Network Slicing in Mobile Networks 74 Figure 14: Comparison Between DPI & Shallow Packet Inspection 77 Figure 15: NGNM SON Use Cases 85 Figure 16: SELFNET's SON Implementation Framework 93 Figure 17: AT&T's SON Implementation 97 Figure 18: Elisa's In-House SON Solution 104 Figure 19: KDDI's Artificial Intelligence-Assisted Automated Network Operation System 110 Figure 20: Orange's Vision for Cognitive PBSM (Policy Based SON Management) 116 Figure 21: SK Telecom's Fast Data Platform for QoE-Based Automatic Network Optimization 120 Figure 22: Telefónica's SON Deployment Roadmap From 4G To 5G Rollouts 124 Figure 23: TIM's Open SON Architecture 127 Figure 24: SON Future Roadmap: 2019 - 2030 136 Figure 25: Wireless Network Infrastructure Value Chain 139 Figure 26: Global SON & Mobile Network Optimization Revenue: 2019 - 2030 ($ Million) 336 Figure 27: Global SON Revenue: 2019 - 2030 ($ Million) 337 Figure 28: Global SON Revenue by Network Segment: 2019 - 2030 ($ Million) 337 Figure 29: Global SON Revenue in the RAN Segment: 2019 - 2030 ($ Million) 338 Figure 30: Global SON Revenue in the Mobile Core Segment: 2019 - 2030 ($ Million) 338 Figure 31: Global SON Revenue in the Transport (Backhaul & Fronthaul) Segment: 2019 - 2030 ($ Million) 339 Figure 32: Global SON Revenue by Architecture: 2019 - 2030 ($ Million) 339 Figure 33: Global C-SON Revenue: 2019 - 2030 ($ Million) 340 Figure 34: Global D-SON Revenue: 2019 - 2030 ($ Million) 340 Figure 35: Global SON Revenue by Access Network Technology: 2019 - 2030 ($ Million) 341 Figure 36: Global 2G & 3G SON Revenue: 2019 - 2030 ($ Million) 341 Figure 37: Global LTE SON Revenue: 2019 - 2030 ($ Million) 342 Figure 38: Global 5G SON Revenue: 2020 - 2030 ($ Million) 342 Figure 39: Global Wi-Fi & Other Access Technology SON Revenue: 2019 - 2030 ($ Million) 343 Figure 40: SON Revenue by Region: 2019 - 2030 ($ Million) 343 Figure 41: Global Conventional Mobile Network Planning & Optimization Revenue: 2019 - 2030 ($ Million) 344 Figure 42: Conventional Mobile Network Planning & Optimization Revenue by Region: 2019 - 2030 ($ Million) 344 Figure 43: Asia Pacific SON Revenue: 2019 - 2030 ($ Million) 345 Figure 44: Asia Pacific Conventional Mobile Network Planning & Optimization Revenue: 2019 - 2030 ($ Million) 345 Figure 45: Eastern Europe SON Revenue: 2019 - 2030 ($ Million) 346 Figure 46: Eastern Europe Conventional Mobile Network Planning & Optimization Revenue: 2019 - 2030 ($ Million) 346 Figure 47: Latin & Central America SON Revenue: 2019 - 2030 ($ Million) 347 Figure 48: Latin & Central America Conventional Mobile Network Planning & Optimization Revenue: 2019 - 2030 ($ Million) 347 Figure 49: Middle East & Africa SON Revenue: 2019 - 2030 ($ Million) 348 Figure 50: Middle East & Africa Conventional Mobile Network Planning & Optimization Revenue: 2019 - 2030 ($ Million) 348 Figure 51: North America SON Revenue: 2019 - 2030 ($ Million) 349 Figure 52: North America Conventional Mobile Network Planning & Optimization Revenue: 2019 - 2030 ($ Million) 349 Figure 53: Western Europe SON Revenue: 2019 - 2030 ($ Million) 350 Figure 54: Western Europe Conventional Mobile Network Planning & Optimization Revenue: 2019 - 2030 ($ Million) 350 Figure 55: SON Associated OpEx Savings by Region: 2019 - 2030 ($ Million) 363
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