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SON (Self-Organizing Networks) in the 5G Era: 2019 - 2030 - Opportunities, Challenges, Strategies & Forecasts

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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