SON (Self-Organizing Networks) in the 5G Era: 2019 – 2030 – Opportunities, Challenges, Strategies & Forecasts
Report Code: KNJ00007 | No. of Pages: 367 | Category: Telecom and IT
Publisher: SnS Telecom | Date of Publish: Sep-2018
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
AIRCOM International
AirHop Communications
Airspan Networks
Allot Communications
Alpha Networks
Altiostar Networks
Alvarion Technologies
Anritsu Corporation
Arcadyan Technology Corporation
ARIB (Association of Radio Industries and Businesses, Japan)
Arista Networks
ARRIS International
Artemis Networks
Artiza Networks
ASUS (ASUSTeK Computer)
ATIS (Alliance for Telecommunications Industry Solutions, United States)
Baicells Technologies
BCE (Bell Canada)
Benu Networks
Bharti Airtel
BLiNQ Networks
Casa Systems
CBNL (Cambridge Broadband Networks Limited)
CCI (Communication Components, Inc.)
CCS (Cambridge Communication Systems)
CCSA (China Communications Standards Association)
CelPlan Technologies
Cisco Systems
Citrix Systems
Collision Communications
Datang Mobile
Dell Technologies
Digi Communications
D-Link Corporation
ECE (European Communications Engineering)
EDX Wireless
Elisa Automate
ETRI (Electronics & Telecommunications Research Institute, South Korea)
ETSI (European Telecommunications Standards Institute)
Federated Wireless
Flash Networks
Fujian Sunnada Network Technology
Gemtek Technology
General Dynamics Mission Systems
Globe Telecom
GoNet Systems
GWT (Global Wireless Technologies)
HCL Technologies
Hitachi Vantara
iBwave Solutions
Intel Corporation
Intracom Telecom
ITRI (Industrial Technology Research Institute, Taiwan)
JRC (Japan Radio Company)
Juni Global
Juniper Networks
KDDI Corporation
Key Bridge
Keysight Technologies
KKTCell (Kuzey Kıbrıs Turkcell)
Koonsys Radiocommunications
Kumu Networks
Lemko Corporation
life:) Belarus
lifecell Ukraine
Linux Foundation
LS telcom
Luminate Wireless
Marvell Technology Group
Mavenir Systems
Mimosa Networks
MitraStar Technology Corporation
Mojo Networks
Nash Technologies
NEC Corporation
NetScout Systems
New Postcom Equipment Company
Nexus Telecom
NGMN Alliance
Nokia Networks
Nomor Research
NuRAN Wireless
Nutaq Innovation
NXP Semiconductors
Oceus Networks
Parallel Wireless
Persistent Systems
Quanta Computer
Radisys Corporation
Ranplan Wireless Network Design
Red Hat
RED Technologies
Redline Communications
Reliance Industries
Rivada Networks
Rohde & Schwarz
Ruckus Wireless
Saguna Networks
Samji Electronics Company
SerComm Corporation
Seven Networks
Siklu Communication
SK Telecom
SK Telesys
Small Cell Forum
Spectrum Effect
SpiderCloud Wireless
Star Solutions
Systemics Group
Tarana Wireless
Tech Mahindra
Tecore Networks
TEKTELIC Communications
Telefónica Group
Telrad Networks
TEOCO Corporation
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
Vasona Networks
Verizon Communications
VHA (Vodafone Hutchison Australia)
Viavi Solutions
Vodafone Germany
Vodafone Group
Vodafone Ireland
Vodafone Spain
Vodafone UK
WBA (Wireless Broadband Alliance)
Wireless DNA
WNC (Wistron NeWeb Corporation)
Zyxel Communications Corporation
Table of Contents 
1 Chapter 1: Introduction
1.1 Executive Summary
1.2 Topics Covered
1.3 Forecast Segmentation
1.4 Key Questions Answered
1.5 Key Findings
1.6 Methodology
1.7 Target Audience
1.8 Companies & Organizations Mentioned
2 Chapter 2: SON & Mobile Network Optimization Ecosystem
2.1 Conventional Mobile Network Optimization
2.1.1 Network Planning
2.1.2 Measurement Collection: Drive Tests, Probes and End User Data
2.1.3 Post-Processing, Optimization & Policy Enforcement
2.2 The SON (Self-Organizing Network) Concept
2.2.1 What is SON?
2.2.2 The Need for SON
2.3 Functional Areas of SON
2.3.1 Self-Configuration
2.3.2 Self-Optimization
2.3.3 Self-Healing
2.3.4 Self-Protection
2.3.5 Self-Learning
2.4 Market Drivers for SON Adoption
2.4.1 The 5G Era: Continued Mobile Network Infrastructure Investments
2.4.2 Optimization in Multi-RAN & HetNet Environments
2.4.3 OpEx & CapEx Reduction: The Cost Savings Potential
2.4.4 Improving Subscriber Experience and Churn Reduction
2.4.5 Power Savings: Towards Green Mobile Networks
2.4.6 Alleviating Congestion with Traffic Management
2.4.7 Enabling Large-Scale Small Cell Rollouts
2.4.8 Growing Adoption of Private LTE & 5G-Ready Networks
2.5 Market Barriers for SON Adoption
2.5.1 Complexity of Implementation
2.5.2 Reorganization & Changes to Standard Engineering Procedures
2.5.3 Lack of Trust in Automation
2.5.4 Proprietary SON Algorithms
2.5.5 Coordination Between Distributed and Centralized SON
2.5.6 Network Security Concerns: New Interfaces and Lack of Monitoring
3 Chapter 3: SON Technology, Use Cases & Implementation Architectures
3.1 Where Does SON Sit Within a Mobile Network?
3.1.1 RAN
3.1.2 Mobile Core
3.1.3 Transport (Backhaul & Fronthaul)
3.1.4 Device-Assisted SON
3.2 SON Architecture
3.2.1 C-SON (Centralized SON)
3.2.2 D-SON (Distributed SON)
3.2.3 H-SON (Hybrid SON)
3.3 SON Use-Cases
3.3.1 Self-Configuration of Network Elements
3.3.2 Automatic Connectivity Management
3.3.3 Self-Testing of Network Elements
3.3.4 Self-Recovery of Network Elements/Software
3.3.5 Self-Healing of Board Faults
3.3.6 Automatic Inventory
3.3.7 ANR (Automatic Neighbor Relations)
3.3.8 PCI (Physical Cell ID) Configuration
3.3.9 CCO (Coverage & Capacity Optimization)
3.3.10 MRO (Mobility Robustness Optimization)
3.3.11 MLB (Mobility Load Balancing)
3.3.12 RACH (Random Access Channel) Optimization
3.3.13 ICIC (Inter-Cell Interference Coordination)
3.3.14 eICIC (Enhanced ICIC)
3.3.15 Energy Savings
3.3.16 COD/COC (Cell Outage Detection & Compensation)
3.3.17 MDT (Minimization of Drive Tests)
3.3.18 AAS (Adaptive Antenna Systems) & Massive MIMO
3.3.19 Millimeter Wave Links in 5G NR (New Radio) Networks
3.3.20 Self-Configuration & Optimization of Small Cells
3.3.21 Optimization of DAS (Distributed Antenna Systems)
3.3.22 RAN Aware Traffic Shaping
3.3.23 Traffic Steering in HetNets
3.3.24 Optimization of NFV-Based Networking
3.3.25 Auto-Provisioning of Transport Links
3.3.26 Transport Network Bandwidth Optimization
3.3.27 Transport Network Interference Management
3.3.28 Self-Protection
3.3.29 SON Coordination Management
3.3.30 Seamless Vendor Infrastructure Swap
3.3.31 Dynamic Spectrum Management & Allocation
3.3.32 Network Slice Optimization
3.3.33 Cognitive & Self-Learning Networks
4 Chapter 4: Key Trends in Next-Generation LTE & 5G SON Implementations
4.1 Big Data & Advanced Analytics
4.1.1 Maximizing the Benefits of SON with Big Data
4.1.2 The Importance of Predictive & Behavioral Analytics
4.2 Artificial Intelligence & Machine Learning
4.2.1 Towards Self-Learning SON Engines with Machine Learning
4.2.2 Deep Learning: Enabling "Zero-Touch" Mobile Networks
4.3 NFV (Network Functions Virtualization)
4.3.1 Enabling the SON-Driven Deployment of VNFs (Virtualized Network Functions)
4.4 SDN (Software Defined Networking) & Programmability
4.4.1 Using the SDN Controller as a Platform for SON in Transport Networks
4.5 Cloud Computing
4.5.1 Facilitating C-SON Scalability & Elasticity
4.6 Small Cells, HetNets & RAN Densification
4.6.1 Plug & Play Small Cells
4.6.2 Coordinating UDNs (Ultra Dense Networks) with SON
4.7 C-RAN (Centralized RAN) & Cloud RAN
4.7.1 Efficient Resource Utilization in C-RAN Deployments with SON
4.8 Unlicensed & Shared Spectrum Usage
4.8.1 Dynamic Management of Spectrum with SON
4.9 MEC (Multi-Access Edge Computing)
4.9.1 Potential Synergies with SON
4.10 Network Slicing
4.10.1 Use of SON Mechanisms for Network Slicing in 5G Networks
4.11 Other Trends & Complementary Technologies
4.11.1 Alternative Carrier/Private LTE & 5G-Ready Networks
4.11.2 FWA (Fixed Wireless Access)
4.11.3 DPI (Deep Packet Inspection)
4.11.4 Digital Security for Self-Protection
4.11.5 SON Capabilities for IoT Applications
4.11.6 User-Based Profiling & Optimization for Vertical 5G Applications
4.11.7 Addressing D2D (Device-to-Device) Communications & New Use Cases
5 Chapter 5: Standardization, Regulatory & Collaborative Initiatives
5.1 3GPP (Third Generation Partnership Project)
5.1.1 Standardization of SON Capabilities for 3GPP Networks
5.1.2 Release 8
5.1.3 Release 9
5.1.4 Release 10
5.1.5 Release 11
5.1.6 Release 12
5.1.7 Releases 13 & 14
5.1.8 Releases 15, 16 & Beyond
5.1.9 Implementation Approach for 3GPP-Specified SON Features
5.2 NGMN Alliance
5.2.1 Conception of the SON Initiative
5.2.2 Functional Areas and Requirements
5.2.3 Implementation Approach: Focus on H-SON
5.2.4 Recommendations for Multi-Vendor SON Deployment
5.2.5 SON Capabilities for 5G Network Deployment, Operation & Management
5.3 ETSI (European Telecommunications Standards Institute)
5.3.1 ENI ISG (Experiential Networked Intelligence Industry Specification Group)
5.4 Linux Foundation's ONAP (Open Network Automation Platform)
5.4.1 ONAP Support for SON in 5G Networks
5.5 OSSii (Operations Support Systems Interoperability Initiative)
5.5.1 Enabling Multi-Vendor SON Interoperability
5.6 Small Cell Forum
5.6.1 Release 7: Focus on SON for Small Cells
5.6.2 SON API
5.6.3 X2 Interoperability
5.7 WBA (Wireless Broadband Alliance)
5.7.1 SON Integration in Carrier Wi-Fi Guidelines
5.8 CableLabs
5.8.1 Wi-Fi RRM (Radio Resource Management)/SON
5.9 5G PPP (5G Infrastructure Public Private Partnership) & European Union Projects
5.9.1 SELFNET (Framework for Self-Organized Network Management in Virtualized and Software Defined Networks)
5.9.2 SEMAFOUR (Self-Management for Unified Heterogeneous Radio Access Networks)
5.9.3 SOCRATES (Self-Optimization and Self-Configuration in Wireless Networks)
5.9.4 COGNET (Building an Intelligent System of Insights and Action for 5G Network Management)
6 Chapter 6: SON Deployment Case Studies
6.1 AT&T
6.1.1 Vendor Selection
6.1.2 SON Deployment Review
6.1.3 Results & Future Plans
6.2 BCE (Bell Canada)
6.2.1 Vendor Selection
6.2.2 SON Deployment Review
6.2.3 Results & Future Plans
6.3 Bharti Airtel
6.3.1 Vendor Selection
6.3.2 SON Deployment Review
6.3.3 Results & Future Plans
6.4 Elisa
6.4.1 Vendor Selection
6.4.2 SON Deployment Review
6.4.3 Results & Future Plans
6.5 Globe Telecom
6.5.1 Vendor Selection
6.5.2 SON Deployment Review
6.5.3 Results & Future Plans
6.6 KDDI Corporation
6.6.1 Vendor Selection
6.6.2 SON Deployment Review
6.6.3 Results & Future Plans
6.7 MegaFon
6.7.1 Vendor Selection
6.7.2 SON Deployment Review
6.7.3 Results & Future Plans
6.8 Orange
6.8.1 Vendor Selection
6.8.2 SON Deployment Review
6.8.3 Results & Future Plans
6.9 Singtel
6.9.1 Vendor Selection
6.9.2 SON Deployment Review
6.9.3 Results & Future Plans
6.10 SK Telecom
6.10.1 Vendor Selection
6.10.2 SON Deployment Review
6.10.3 Results & Future Plans
6.11 Telefónica Group
6.11.1 Vendor Selection
6.11.2 SON Deployment Review
6.11.3 Results & Future Plans
6.12 TIM (Telecom Italia Mobile)
6.12.1 Vendor Selection
6.12.2 SON Deployment Review
6.12.3 Results & Future Plans
6.13 Turkcell
6.13.1 Vendor Selection
6.13.2 SON Deployment Review
6.13.3 Results & Future Plans
6.14 Verizon Communications
6.14.1 Vendor Selection
6.14.2 SON Deployment Review
6.14.3 Results & Future Plans
6.15 Vodafone Group
6.15.1 Vendor Selection
6.15.2 SON Deployment Review
6.15.3 Results & Future Plans
7 Chapter 7: Future Roadmap & Value Chain
7.1 Future Roadmap
7.1.1 Pre-2020: Addressing Customer QoE, Network Densification & Early 5G Rollouts
7.1.2 2020 – 2025: Towards Advanced Machine Learning Based SON Implementations
7.1.3 2025 – 2030: Enabling Near Zero-Touch & Automated 5G Networks
7.2 Value Chain
7.3 Embedded Technology Ecosystem
7.3.1 Chipset Developers
7.3.2 Embedded Component/Software Providers
7.4 RAN Ecosystem
7.4.1 Macrocell RAN OEMs
7.4.2 Pure-Play Small Cell OEMs
7.4.3 Wi-Fi Access Point OEMs
7.4.4 DAS & Repeater Solution Providers
7.4.5 C-RAN Solution Providers
7.4.6 Other Technology Providers
7.5 Transport Networking Ecosystem
7.5.1 Backhaul & Fronthaul Solution Providers
7.6 Mobile Core Ecosystem
7.6.1 Mobile Core Solution Providers
7.7 Connectivity Ecosystem
7.7.1 Mobile Operators
7.7.2 Wi-Fi Connectivity Providers
7.7.3 SCaaS (Small-Cells-as-a-Service) Providers
7.8 SON Ecosystem
7.8.1 SON Solution Providers
7.9 SDN & NFV Ecosystem
7.9.1 SDN & NFV Providers
7.10 MEC Ecosystem
7.10.1 MEC Specialists
8 Chapter 8: Key Ecosystem Players
8.1 Accedian Networks
8.2 Accelleran
8.3 AirHop Communications
8.4 Airspan Networks
8.5 Allot Communications
8.6 Alpha Networks
8.7 Altiostar Networks
8.8 Altran/Aricent
8.9 Alvarion Technologies/SuperCom
8.10 Amdocs
8.11 Anritsu Corporation
8.12 Arcadyan Technology Corporation
8.13 Argela/Netsia
8.14 Artemis Networks
8.15 Artiza Networks
8.16 ASOCS
8.17 ASUS (ASUSTeK Computer)
8.18 ATDI
8.19 Baicells Technologies
8.20 Benu Networks
8.21 BoostEdge
8.22 Broadcom
8.23 Casa Systems
8.24 CBNL (Cambridge Broadband Networks Limited)
8.25 CCI (Communication Components, Inc.)/BLiNQ Networks
8.26 CCS (Cambridge Communication Systems)
8.27 CellOnyx
8.28 Cellwize
8.29 CelPlan Technologies
8.30 Celtro
8.31 Cisco Systems
8.32 Citrix Systems
8.33 Collision Communications
8.34 Comarch
8.35 CommAgility
8.36 CommScope
8.37 CommProve
8.38 Contela
8.39 Continual
8.40 Coriant
8.41 Corning/SpiderCloud Wireless
8.42 Datang Mobile
8.43 Dell Technologies
8.44 Digitata
8.45 D-Link Corporation
8.46 ECE (European Communications Engineering)
8.47 EDX Wireless
8.48 Elisa Automate
8.49 Empirix
8.50 Equiendo
8.51 Ercom
8.52 Ericsson
8.53 ETRI (Electronics & Telecommunications Research Institute, South Korea)
8.54 EXFO/Astellia
8.55 Facebook
8.56 Fairspectrum
8.57 Federated Wireless
8.58 Flash Networks
8.59 Forsk
8.60 Fujian Sunnada Network Technology
8.61 Fujitsu
8.62 Galgus
8.63 Gemtek Technology
8.64 General Dynamics Mission Systems
8.65 GenXComm
8.66 GoNet Systems
8.67 Google/Alphabet
8.68 Guavus/Thales
8.69 GWT (Global Wireless Technologies)
8.70 HCL Technologies
8.71 Hitachi
8.72 Huawei
8.73 iBwave Solutions
8.74 InfoVista
8.75 Innovile
8.76 InnoWireless/Qucell/Accuver
8.77 Intel Corporation
8.78 InterDigital
8.79 Intracom Telecom
8.80 ip.access
8.81 ITRI (Industrial Technology Research Institute, Taiwan)
8.82 JRC (Japan Radio Company)
8.83 Juni Global
8.84 Juniper Networks
8.85 Keima
8.86 Key Bridge
8.87 Keysight Technologies/Ixia
8.88 Kleos
8.89 Koonsys Radiocommunications
8.90 Kumu Networks
8.91 Lemko Corporation
8.92 Linksys
8.93 LS telcom
8.94 Luminate Wireless
8.95 LuxCarta
8.96 Marvell Technology Group/Cavium
8.97 Mavenir Systems
8.98 Mimosa Networks
8.99 MitraStar Technology Corporation
8.100 Mojo Networks/Arista Networks
8.101 Mosaik
8.102 Nash Technologies
8.103 NEC Corporation
8.104 NetScout Systems
8.105 New Postcom Equipment Company
8.106 Node-H
8.107 Nokia Networks
8.108 Nomor Research
8.109 NuRAN Wireless/Nutaq Innovation
8.110 NXP Semiconductors
8.111 Oceus Networks
8.112 P.I.Works
8.113 Parallel Wireless
8.114 Persistent Systems
8.115 PHAZR
8.116 Phluido
8.117 Polystar
8.118 Potevio
8.119 Qualcomm
8.120 Quanta Computer
8.121 RADCOM
8.122 Radisys Corporation/Reliance Industries
8.123 Ranplan Wireless Network Design
8.124 RED Technologies
8.125 Redline Communications
8.126 Rivada Networks
8.127 Rohde & Schwarz
8.128 Ruckus Wireless/ARRIS International
8.129 Saguna Networks
8.130 Samji Electronics Company
8.131 Samsung
8.133 SerComm Corporation
8.134 Seven Networks
8.135 Siklu Communication
8.138 SK Telesys
8.139 Spectrum Effect
8.140 Star Solutions
8.141 Systemics Group
8.142 Tarana Wireless
8.143 Tech Mahindra
8.144 Tecore Networks
8.145 TEKTELIC Communications
8.146 Telrad Networks
8.147 TEOCO Corporation
8.148 Teragence
8.149 TI (Texas Instruments)
8.150 TP-Link Technologies
8.151 TTG International
8.152 Tulinx
8.153 Vasona Networks
8.154 Viavi Solutions
8.155 VMWare
8.156 WebRadar
8.157 Wireless DNA
8.158 WNC (Wistron NeWeb Corporation)
8.160 XCellAir/Fontech
8.161 Z-Com
8.162 ZTE
8.163 Zyxel Communications Corporation
9 Chapter 9: Market Sizing & Forecasts
9.1 SON & Mobile Network Optimization Revenue
9.2 SON Revenue
9.3 SON Revenue by Network Segment
9.3.1 RAN
9.3.2 Mobile Core
9.3.3 Transport (Backhaul & Fronthaul)
9.4 SON Revenue by Architecture: Centralized vs. Distributed
9.4.1 C-SON
9.4.2 D-SON
9.5 SON Revenue by Access Network Technology
9.5.1 2G & 3G
9.5.2 LTE
9.5.3 5G
9.5.4 Wi-Fi
9.6 SON Revenue by Region
9.7 Conventional Mobile Network Planning & Optimization Revenue
9.8 Conventional Mobile Network Planning & Optimization Revenue by Region
9.9 Asia Pacific
9.9.1 SON
9.9.2 Conventional Mobile Network Planning & Optimization
9.10 Eastern Europe
9.10.1 SON
9.10.2 Conventional Mobile Network Planning & Optimization
9.11 Latin & Central America
9.11.1 SON
9.11.2 Conventional Mobile Network Planning & Optimization
9.12 Middle East & Africa
9.12.1 SON
9.12.2 Conventional Mobile Network Planning & Optimization
9.13 North America
9.13.1 SON
9.13.2 Conventional Mobile Network Planning & Optimization
9.14 Western Europe
9.14.1 SON
9.14.2 Conventional Mobile Network Planning & Optimization
10 Chapter 10: Conclusion & Strategic Recommendations
10.1 Why is the Market Poised to Grow?
10.2 Competitive Industry Landscape: Acquisitions, Alliances & Consolidation
10.3 Evaluating the Practical Benefits of SON
10.4 End-to-End SON: Moving Towards Mobile Core and Transport Networks
10.5 Growing Adoption of SON Capabilities for Wi-Fi
10.6 The Importance of Artificial Intelligence & Machine Learning
10.7 QoE-Based SON Platforms: Optimizing End User Experience
10.8 Enabling Network Slicing & Advanced Capabilities for 5G Networks
10.9 Greater Focus on Self-Protection Capabilities
10.10 Addressing IoT Optimization
10.11 Managing Unlicensed & Shared Spectrum
10.12 Easing the Deployment of Private & Enterprise LTE/5G-Ready Networks
10.13 Assessing the Impact of SON on Optimization & Field Engineers
10.14 SON Associated OpEx Savings: The Numbers
10.15 The C-SON Versus D-SON Debate
10.16 Strategic Recommendations
10.16.1 SON Solution Providers
10.16.2 Mobile Operators

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