Home >> Telecommunications >> Consumer Electronics >> Heavy Industry >>

The Self-Organizing Networks (SON) Ecosystem: 2014 - 2020

Published: Mar-2014 | Format: PDF | SNS Telecom & IT | Number of pages: 186 | Code: MRS - 775

Self-Organizing Network (SON) technology minimizes the lifecycle cost of running a wireless carrier network by eliminating manual configuration of equipment at the time of deployment, right through to dynamically optimizing performance and troubleshooting during operation. This can significantly reduce the cost of the carrier’s services, improving the OpEx to revenue ratio.

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

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

Despite challenges relating to implementation complexities and multi-vendor interoperability, SON revenue is expected to grow to more than $3 Billion by the end of 2016, exceeding conventional mobile network optimization revenue by over 20%.

The “Self-Organizing Networks (SON) Ecosystem: 2014 – 2020” report presents an in-depth assessment of the SON and associated mobile network optimization ecosystem including key market drivers, challenges, OpEx and CapEx savings potential, use cases, SON deployment case studies, future roadmap, value chain, vendor analysis and strategies. The report also presents revenue forecasts for both SON and conventional mobile network optimization, along with individual projections for 8 SON submarkets from 2014 through to 2020. Historical figures are also presented for 2010, 2011, 2012 and 2013.

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

Key Findings:

The report has the following key findings:

  • Despite challenges relating to implementation complexities and multi-vendor interoperability, SON revenue is expected to grow to more than $3 Billion by the end of 2016, exceeding conventional mobile network optimization revenue by over 20%
  • Driven by large scale TD-LTE rollouts and ongoing SON deployments, the Asia Pacific region will account for nearly 40% of the global mobile network optimization market by 2016
  • SNS Research estimates that SON can enable wireless carriers to save up to 35% of their electrical power consumption by dynamically by activating and deactivating RAN nodes in line with the changing traffic and user distribution profile
  • SNS Research estimates that a Tier 1 wireless carrier can save as much as 32% of its overall OpEx by employing SON across the RAN, mobile core and mobile backhaul segments of the network
  • Wireless carriers have reported up to a 40% reduction in dropped calls and over 20% higher data rates with SON implementation
  • Infrastructure and software incumbents are aggressively eyeing on acquisitions of smaller established C-SON players to accelerate their early entry path into the C-SON market


Topics Covered:

The report covers the following topics:

  • Conventional mobile network planning & optimization
  • SON technology and architecture
  • Key benefits and market drivers of SON
  • Challenges to SON adoption
  • SON use cases
  • SON deployment case studies
  • Company profiles and strategies of over 60 SON ecosystem players
  • OpEx and CapEx saving analysis of SON
  • Wireless network infrastructure spending and traffic projections
  • Wireless network infrastructure industry roadmap and value chain
  • Future roadmap of the SON ecosystem
  • Convergence of SON with other technologies (such as Big Data analytics)
  • Strategic recommendations for SON solution providers, wireless infrastructure OEMs and wireless carriers
  • Market analysis and forecasts from 2014 till 2020


Forecast Segmentation:

Market forecasts and historical figures are provided for each of the following submarkets and their subcategories:

  • Mobile Network Optimization
  • SON
  • Conventional Mobile Network Planning & Optimization
  • SON Submarkets
  • Macrocell RAN
  • HetNet/Small Cell RAN
  • Mobile Core
  • Mobile Backhaul
  • SON Architecture Submarkets
  • C-SON (Centralized SON)
  • D-SON (Distributed SON)
  • SON Wireless Network Generation Submarkets
  • 2G/3G
  • 4G
  • SON CapEx & OpEx Savings Submarkets
  • RAN
  • Mobile Core
  • Mobile Backhaul
  • Regional Submarkets
  • 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 and mobile network optimization ecosystem?
  • How is the ecosystem evolving by segment and region?
  • What will the market size be in 2020 and at what rate will it grow?
  • What trends, challenges and barriers are influencing its growth?
  • Who are the key SON vendors and what are their strategies?
  • What is the outlook for QoE based SON solutions?
  • What is the outlook for C-SON and D-SON adoption?
  • What is the outlook for SON associated OpEx savings by region?
  • How will SON investments compare with those on traditional mobile network optimization?
  • What opportunities exist for SON in mobile core and mobile backhaul?
  • How will SON use cases evolve overtime in 3GPP releases?
  • Which regions will see the highest number of SON investments?
  • How much will wireless carriers invest in SON solutions?"


Countires Covered

  • Afghanistan
  • Albania
  • Algeria
  • Andorra
  • Angola
  • Anguilla
  • Antigua & Barbuda
  • Argentina
  • Armenia
  • Aruba
  • Australia
  • Austria
  • Azerbaijan
  • Bahamas
  • Bahrain
  • Bangladesh
  • Barbados
  • Belarus
  • Belgium
  • Belize
  • Benin
  • Bermuda
  • Bhutan
  • Bolivia
  • Bosnia Herzegovina
  • Botswana
  • Brazil
  • British Virgin Islands
  • Brunei
  • Bulgaria
  • Burkina Faso
  • Burundi
  • Cambodia
  • Cameroon
  • Canada
  • Cape Verde
  • Cayman Islands
  • Central African Republic
  • Chad
  • Chile
  • China
  • Cocos Islands
  • Colombia
  • Comoros Islands
  • Congo
  • Cook Islands
  • Costa Rica
  • Côte d'Ivoire
  • Croatia
  • Cuba
  • Cyprus
  • Czech Republic
  • Democratic Rep of Congo (ex-Zaire)
  • Denmark
  • Djibouti
  • Dominica
  • Dominican Republic
  • East Timor
  • Ecuador
  • Egypt
  • El Salvador
  • Equatorial Guinea
  • Eritrea
  • Estonia
  • Ethiopia
  • Faroe Islands
  • Federated States of Micronesia
  • Fiji
  • Finland
  • France
  • French Guiana
  • French Polynesia (ex-Tahiti)
  • French West Indies
  • Gabon
  • Gambia
  • Georgia
  • Germany
  • Ghana
  • Gibraltar
  • Greece
  • Greenland
  • Grenada
  • Guam
  • Guatemala
  • Guernsey
  • Guinea Republic
  • Guinea-Bissau
  • Guyana
  • Haiti
  • Honduras
  • Hong Kong
  • Hungary
  • Iceland
  • India
  • Indonesia
  • Iran
  • Iraq
  • Ireland
  • Isle of Man
  • Israel
  • Italy
  • Jamaica
  • Japan
  • Jersey
  • Jordan
  • Kazakhstan
  • Kenya
  • Kirghizstan
  • Kiribati
  • Korea
  • Kosovo
  • Kuwait
  • Laos
  • Latvia
  • Lebanon
  • Lesotho
  • Liberia
  • Libya
  • Liechtenstein
  • Lithuania
  • Luxembourg
  • Macau
  • Macedonia
  • Madagascar
  • Malawi
  • Malaysia
  • Maldives
  • Mali
  • Malta
  • Marshall Islands
  • Mauritania
  • Mauritius
  • Mayotte
  • Mexico
  • Moldova
  • Monaco
  • Mongolia
  • Montenegro
  • Montserrat
  • Morocco
  • Mozambique
  • Myanmar
  • Namibia
  • Nepal
  • Netherlands
  • Netherlands Antilles
  • New Caledonia
  • New Zealand
  • Nicaragua
  • Niger
  • Nigeria
  • Niue
  • North Korea
  • Northern Marianas
  • Norway
  • Oman
  • Pakistan
  • Palau
  • Palestine
  • Panama
  • Papua New Guinea
  • Paraguay
  • Peru
  • Philippines
  • Poland
  • Portugal
  • Puerto Rico
  • Qatar
  • Réunion
  • Romania
  • Russia
  • Rwanda
  • Samoa
  • Samoa (American)
  • Sao Tomé & Principe
  • Saudi Arabia
  • Senegal
  • Serbia
  • Seychelles
  • Sierra Leone
  • Singapore
  • Slovak Republic
  • Slovenia
  • Solomon Islands
  • Somalia
  • South Africa
  • Spain
  • Sri Lanka
  • St Kitts & Nevis
  • St Lucia
  • St Vincent & The Grenadines
  • Sudan
  • Suriname
  • Swaziland
  • Sweden
  • Switzerland
  • Syria
  • Tajikistan
  • Taiwan
  • Tanzania
  • Thailand
  • Togo
  • Tonga
  • Trinidad & Tobago
  • Tunisia
  • Turkey
  • Turkmenistan
  • Turks & Caicos Islands
  • UAE
  • Uganda
  • UK
  • Ukraine
  • Uruguay
  • US Virgin Islands
  • USA
  • Uzbekistan
  • Vanuatu
  • Venezuela
  • Vietnam
  • Yemen
  • Zambia Zimbabwe

Table of Content

1 Chapter 1: Introduction
1.1 Executive Summary
1.2 Topics Covered
1.3 Historical Revenue & 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 Self-Organizing Network (SON) 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
2.4 Market Drivers for SON Adoption
2.4.1 Continued Wireless Network Infrastructure Investments
2.4.2 Optimization in Multi-RAN & HetNet Environments
2.4.3 OpEx & CapEx Reduction: The Cost Saving Potential
2.4.4 Improving Subscriber Experience and Churn Reduction
2.4.5 Power Savings
2.4.6 Enabling Small Cell Deployments
2.4.7 Traffic Management
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 Lack of Operator Control: 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 Mobile Backhaul
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 (Mobile 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 Cell Outage Detection & Compensation
3.3.17 Self-Configuration & Optimization of Small Cells
3.3.18 Optimization of DAS (Distributed Antenna Systems)
3.3.19 RAN Aware Traffic Shaping
3.3.20 Traffic Steering in HetNets
3.3.21 Optimization of Virtualized Network Resources
3.3.22 Auto-Provisioning of Backhaul Links
3.3.23 Backhaul Bandwidth Optimization
3.3.24 Backhaul Interference Management
3.3.25 SON Coordination Management
3.3.26 Seamless Vendor Infrastructure Swap

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

5 Chapter 5: SON Deployment Case Studies
5.1 AT&T Mobility
5.1.1 Vendor Selection & Contract Value
5.1.2 Implemented Use Cases
5.1.3 Results
5.2 SingTel
5.2.1 Vendor Selection & Contract Value
5.2.2 Implemented Use Cases
5.2.3 Results
5.3 TIM Brasil
5.3.1 Vendor Selection & Contract Value
5.3.2 Implemented Use Cases
5.3.3 Results
5.4 KDDI
5.4.1 Vendor Selection & Contract Value
5.4.2 Implemented Use Cases
5.4.3 Results

6 Chapter 6: Industry Roadmap & Value Chain
6.1 Industry Roadmap
6.1.1 Initial LTE FDD Rollouts with D-SON: 2010 - 2011
6.1.2 Rise of the HetNets & C-SON: 2012 - 2013
6.1.3 TD-LTE Deployments & Continued SON Proliferation: 2014 - 2016
6.1.4 “Software Centric” Networking & QoE/QoS Based SON: 2017 - 2019
6.1.5 Start of the 5G Era: 2020 & Beyond
6.2 Value Chain
6.3 Embedded Technology Ecosystem
6.3.1 Chipset Developers
6.3.2 Embedded Component/Software Providers
6.4 RAN Ecosystem
6.4.1 Macrocell RAN OEMs
6.4.2 ‘Pure-Play’ and Specialist Small Cell OEMs
6.4.3 WiFi Access Point OEMs
6.4.4 DAS & Repeater Solution Providers
6.4.5 Cloud RAN Solution Providers
6.4.6 Other Technology & Network Component Providers/Enablers
6.5 Mobile Backhaul Ecosystem
6.5.1 Backhaul Solution Providers
6.6 Mobile Core Ecosystem
6.6.1 Core Network Infrastructure & Software Providers
6.7 Connectivity Ecosystem
6.7.1 2G, 3G & 4G Wireless Carriers
6.7.2 WiFi Connectivity Providers
6.7.3 Small Cells as a Service (SCaaS) Providers
6.8 SON & Mobile Network Optimization Ecosystem
6.8.1 SON Solution Providers
6.8.2 Mobile Network Optimization Solution Providers
6.9 SDN & NFV Ecosystem
6.9.1 SDN & NFV Providers

7 Chapter 7: Vendor Landscape
7.1 Accedian Networks
7.2 Accuver
7.3 AIRCOM International (Acquired by TEOCO)
7.4 AirHop Communications
7.5 Airspan Networks
7.6 Alcatel-Lucent
7.7 Amdocs
7.8 Arcadyan
7.9 Argela
7.10 Aricent
7.11 ARItel
7.12 Ascom
7.13 Astellia
7.14 ATDI
7.15 Avvasi
7.16 Broadcom
7.17 BLiNQ Networks
7.18 Cavium
7.19 CBNL (Cambridge Broadband Networks Limited)
7.20 Cellwize
7.21 Celtro
7.22 CENTRI
7.23 Cisco Systems
7.24 Citrix
7.25 Comarch
7.26 Commsquare
7.27 DTM (Datang Mobile)
7.28 ECE (European Communications Engineering)
7.29 Eden Rock Communications
7.30 Ericsson
7.31 Forsk
7.32 Freescale Semiconductor
7.33 Fujitsu
7.34 Guavus
7.35 Hitachi
7.36 Huawei
7.37 Intel
7.38 InterDigital
7.39 InfoVista
7.40 JDSU
7.41 Lemko
7.42 Lavastorm
7.43 mimoOn
7.44 NEC
7.45 NSN (Nokia Solutions & Networks)
7.46 Optulink
7.47 P.I.Works
7.48 Plano Engineering
7.49 Qualcomm
7.50 Radisys
7.51 RADCOM
7.52 Reverb Networks
7.53 Rohde & Schwarz
7.54 Rorotika
7.55 Samsung
7.56 SEDICOM
7.57 Siklu
7.58 SpiderCloud Wireless
7.59 Tarana Wireless
7.60 Tektronix Communications
7.61 Tellabs
7.62 TEOCO
7.63 Texas Instruments
7.64 Theta Networks
7.65 TTG International
7.66 Tulinx
7.67 WebRadar
7.68 Xceed Technologies
7.69 ZTE

8 Chapter 8: Market Analysis & Forecasts
8.1 SON & Mobile Network Optimization Revenue
8.2 SON Revenue
8.3 SON Revenue by Submarket
8.3.1 SON in Macrocell RAN
8.3.2 SON in HetNet/Small Cell RAN
8.3.3 SON in Mobile Core
8.3.4 SON in Mobile Backhaul
8.4 SON Revenue by Architecture: Centralized vs. Distributed
8.4.1 C-SON
8.4.2 D-SON
8.5 SON Revenue by Wireless Network Generation: 2G/3G vs. 4G
8.5.1 2G/3G SON
8.5.2 4G SON
8.6 SON Revenue by Region
8.7 Conventional Mobile Network Planning & Optimization Revenue
8.8 Conventional Mobile Network Planning & Optimization Revenue by Region
8.9 Asia Pacific
8.9.1 SON
8.9.2 Conventional Mobile Network Planning & Optimization
8.10 Eastern Europe
8.10.1 SON
8.10.2 Conventional Mobile Network Planning & Optimization
8.11 Latin & Central America
8.11.1 SON
8.11.2 Conventional Mobile Network Planning & Optimization
8.12 Middle East & Africa
8.12.1 SON
8.12.2 Conventional Mobile Network Planning & Optimization
8.13 North America
8.13.1 SON
8.13.2 Conventional Mobile Network Planning & Optimization
8.14 Western Europe
8.14.1 SON
8.14.2 Conventional Mobile Network Planning & Optimization

9 Chapter 9: Conclusion & Strategic Recommendations
9.1 Moving Towards QoE Based SON Platforms
9.2 Capitalizing on DPI (Deep Packet Inspection)
9.3 The Convergence of Big Data Analytics & SON
9.4 SON for NFV & SDN: The Push from Wireless Carriers
9.5 Moving Towards Mobile Core and Backhaul
9.6 Assessing the Impact of SON on Optimization & Field Engineers
9.7 SON Associated OpEx Savings: The Numbers
9.8 What SON Capabilities Will 5G Networks Entail?
9.9 The C-SON Versus D-SON Debate
9.10 Strategic Recommendations
9.10.1 SON & Conventional Mobile Network Optimization Solution Providers
9.10.2 Wireless Infrastructure OEMs
9.10.3 Wireless Carriers


List of Figures

Figure 1: Functional Areas of SON with the Mobile Network Lifecycle
Figure 2: Annual Global Throughput of Mobile Network Data Traffic by Region: 2010 – 2020 (Exabytes)
Figure 3: Global Wireless Network Infrastructure Revenue by Submarket: 2010 – 2020 ($ Million)
Figure 4: Global Mobile Network Data Traffic Distribution by Access Network Form Factor: 2010 – 2020 (%)
Figure 5: SON Associated OpEx & CapEx Savings by Network Segment
Figure 6: Potential Areas of SON Implementation
Figure 7: Mobile Backhaul Segmentation by Technology
Figure 8: C-SON (Centralized SON) in a Wireless Carrier Network
Figure 9: D-SON (Distributed SON) in a Wireless Carrier Network
Figure 10: H-SON (Hybrid SON) in a Wireless Carrier Network
Figure 11: NGNM SON Use Cases
Figure 12: The Wireless Network Infrastructure Industry Roadmap: 2014 - 2020
Figure 13: The Wireless Network Infrastructure Value Chain
Figure 14: Embedded Technology Ecosystem Players
Figure 15: Macrocell RAN Ecosystem Players
Figure 16: Specialist Small Cell RAN Ecosystem Players
Figure 17: Carrier WiFi Ecosystem Players
Figure 18: DAS & Repeater Ecosystem Players
Figure 19: Cloud RAN Ecosystem Players
Figure 20: Mobile Backhaul Ecosystem Players
Figure 21: Mobile Core Ecosystem Players
Figure 22: List of LTE Trials & Deployments
Figure 23: SON & Mobile Network Optimization Ecosystem Players
Figure 24: SDN & NFV Ecosystem Players
Figure 25: Global SON & Mobile Network Optimization Revenue: 2010 - 2020 ($ Million)
Figure 26: Global SON Revenue: 2010 - 2020 ($ Million)
Figure 27: Global SON Revenue by Submarket: 2010 - 2020 ($ Million)
Figure 28: Global Macrocell RAN SON Revenue: 2010 - 2020 ($ Million)
Figure 29: Global Small Cell RAN SON Revenue: 2010 - 2020 ($ Million)
Figure 30: Global Mobile Core SON Revenue: 2010 - 2020 ($ Million)
Figure 31: Global Mobile Backhaul SON Revenue: 2010 - 2020 ($ Million)
Figure 32: Global SON Revenue by Architecture: 2010 - 2020 ($ Million)
Figure 33: Global C-SON Revenue: 2010 - 2020 ($ Million)
Figure 34: Global D-SON Revenue: 2010 - 2020 ($ Million)
Figure 35: Global SON Revenue by Wireless Network Generation: 2010 - 2020 ($ Million)
Figure 36: Global 2G/3G SON Revenue: 2010 - 2020 ($ Million)
Figure 37: Global 4G SON Revenue: 2010 - 2020 ($ Million)
Figure 38: SON Revenue by Region: 2010 - 2020 ($ Million)
Figure 39: Global Conventional Mobile Network Planning & Optimization Revenue: 2010 - 2020 ($ Million)
Figure 40: Conventional Mobile Network Planning & Optimization Revenue by Region: 2010 - 2020 ($ Million)
Figure 41: Asia Pacific SON Revenue: 2010 - 2020 ($ Million)
Figure 42: Asia Pacific Conventional Mobile Network Planning & Optimization Revenue: 2010 - 2020 ($ Million)
Figure 43: Eastern Europe SON Revenue: 2010 - 2020 ($ Million)
Figure 44: Eastern Europe Conventional Mobile Network Planning & Optimization Revenue: 2010 - 2020 ($ Million)
Figure 45: Latin & Central America SON Revenue: 2010 - 2020 ($ Million)
Figure 46: Latin & Central America Conventional Mobile Network Planning & Optimization Revenue: 2010 - 2020 ($ Million)
Figure 47: Middle East & Africa SON Revenue: 2010 - 2020 ($ Million)
Figure 48: Middle East & Africa Conventional Mobile Network Planning & Optimization Revenue: 2010 - 2020 ($ Million)
Figure 49: North America SON Revenue: 2010 - 2020 ($ Million)
Figure 50: North America Conventional Mobile Network Planning & Optimization Revenue: 2010 - 2020 ($ Million)
Figure 51: Western Europe SON Revenue: 2010 - 2020 ($ Million)
Figure 52: Western Europe Conventional Mobile Network Planning & Optimization Revenue: 2010 - 2020 ($ Million)
Figure 53: SON Associated OpEx Savings by Region: 2010 - 2020 ($ Million)

Inquiry For Buying

Please fill your details below, to inquire about this report:
Indicates required fields

Request Sample

Please fill your details below, to receive sample report:
Indicates required fields

  • Payment Mode
Single User | $(USD)2500 View Pricing