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

Publication ID: 
SNS0815001
Publication Date: 
August 14, 2015
Pages: 
180
Publisher: 
Signals and Systems Telecom
Countries: 
Global [1]
USD 2,500.00

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Telecom [2]
Telecom Infrastructure & Networks [3]
Description: 
SON (Self-Organizing Network) technology minimizes the lifecycle cost of running a mobile network by eliminating manual configuration of equipment at the time of deployment, right through to dynamically optimizing performance and troubleshooting during operation. This can significantly reduce the cost of the operator鈥檚 services, improving the OpEx to revenue ratio.听
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Amid growing demands for mobile broadband connectivity, mobile operators are keen to capitalize on SON to minimize rollout delays and operational expenditures associated with their ongoing LTE and HetNet deployments.听
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Originally targeted for the RAN (Radio Access Network) segment of mobile networks, SON technology is now also utilized in the mobile core and transport network segments. Furthermore, the SON ecosystem is increasingly witnessing convergence with other technological innovations such as Big Data, predictive analytics and DPI (Deep Packet Inspection).
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Despite challenges relating to implementation complexities and multi-vendor interoperability, SON revenue is expected to grow to more than $4 Billion by the end of 2017, exceeding conventional mobile network optimization revenue by nearly 60%.
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The 鈥淪ON (Self-Organizing Networks) Ecosystem: 2015 鈥� 2030 鈥� Opportunities, Challenges, Strategies & Forecasts鈥� report presents an in-depth assessment of the SON and associated mobile network optimization ecosystem including key market drivers, challenges, OpEx and CapEx savings potential, use cases, SON deployment case studies, future roadmap, value chain, vendor analysis and strategies. The report also presents revenue forecasts for both SON and conventional mobile network optimization, along with individual projections for 7 SON submarkets, 6 regions and 15 countries from 2015 through to 2030.听
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The report comes with an associated Excel datasheet suite covering quantitative data from all numeric forecasts presented in the report.
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Key Findings:
  • The report has the following key findings:
  • Despite challenges relating to implementation complexities and multi-vendor interoperability, SON revenue is expected to grow to more than $4 Billion by the end of 2017, exceeding conventional mobile network optimization revenue by nearly 60%
  • SNS Research estimates that SON can enable wireless carriers to save nearly 40% 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 more than 30% 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 50% reduction in dropped calls and over 20% higher data rates with SON implementation
  • SON platforms are moving from reactive systems to more advanced implementations that incorporate predictive analytics technology to make necessary changes to a network before any degradation occurs
  • Infrastructure and software incumbents are aggressively eyeing on acquisitions of smaller established C-SON players to accelerate their early entry path into the C-SON market
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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 70 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 Big Data and predictive analytics
  • Strategic recommendations for SON solution providers, wireless infrastructure OEMs and wireless carriers
  • Market analysis and forecasts from 2015 till 2030
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Forecast Segmentation:
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Market forecasts and historical figures are provided for each of the following submarkets and their subcategories:
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Mobile Network Optimization
  • SON
  • Conventional Mobile Network Planning & Optimization
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SON Network Segment Submarkets
  • RAN
  • Mobile Core
  • Mobile Backhaul & Transport
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SON Architecture Submarkets
  • C-SON (Centralized SON)
  • D-SON (Distributed SON)
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SON Wireless Network Generation Submarkets
  • 2G & 3G
  • 4G & Beyond
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Regional Submarkets
  • Asia Pacific
  • Eastern Europe
  • Latin & Central America
  • Middle East & Africa
  • North America
  • Western Europe
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Country Markets
  • Australia
  • Brazil
  • Canada
  • China
  • France
  • Germany
  • India
  • Italy
  • Japan
  • Russia
  • South Korea
  • Spain
  • Taiwan
  • UK
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Key Questions Answered:
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  • 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?听
  • 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?
Table Of Contents: 
Table of Contents
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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
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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
2.4
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
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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 & Transport
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 Transport Links
3.3.23
Transport Network Bandwidth Optimization
3.3.24
Transport Network Interference Management
3.3.25
SON Coordination Management
3.3.26
Seamless Vendor Infrastructure Swap
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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
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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
5.5
SK Telecom
5.5.1
Vendor Selection & Contract Value
5.5.2
Implemented Use Cases
5.5.3
Results
5.6
Globe Telecom
5.6.1
Vendor Selection & Contract Value
5.6.2
Implemented Use Cases
5.6.3
Results
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6
Chapter 6: Industry Roadmap & Value Chain
6.1
Industry Roadmap
6.1.1
Large Scale Adoption of SON Technology: 2015 - 2020
6.1.2
Towards QoE/QoS Based End-to-End SON: 2020 - 2025
6.1.3
Continued Investments to Support 5G Rollouts: 2025 - 2030
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
C-RAN Solution Providers
6.4.6
Other Technology & Network Component Providers/Enablers
6.5
Mobile Backhaul & Fronthaul Ecosystem
6.5.1
Backhaul & Fronthaul 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
SCaaS (Small Cells as a Service) 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
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7
Chapter 7: Vendor Landscape
7.1
Accedian Networks
7.2
Accuver
7.3
AirHop Communications
7.4
Airspan Networks
7.5
Alcatel-Lucent
7.6
Amdocs
7.7
Anite
7.8
Arcadyan
7.9
Argela
7.10
Aricent
7.11
ARItel
7.12
Ascom
7.13
Astellia
7.14
ATDI
7.15
Avago Technologies
7.16
Avvasi
7.17
BLiNQ Networks
7.18
Cavium
7.19
CBNL (Cambridge Broadband Networks Limited)
7.20
CellMining
7.21
Cellwize
7.22
Celtro Communications
7.23
CENTRI
7.24
Cisco Systems
7.25
Citrix Systems
7.26
Comarch
7.27
CommAgility
7.28
Commsquare
7.29
Coriant
7.30
Datang Mobile
7.31
ECE (European Communications Engineering)
7.32
Ericsson
7.33
Flash Networks
7.34
Forsk
7.35
Fujitsu
7.36
Guavus
7.37
Hitachi
7.38
Huawei
7.39
InfoVista
7.40
Intel Corporation
7.41
InterDigital
7.42
ip.access
7.43
Lavastorm
7.44
Lemko Corporation
7.45
NEC Corporation
7.46
Nokia Networks
7.47
NXP Semiconductors
7.48
Optulink
7.49
P.I.Works
7.50
Plano Engineering
7.51
Qualcomm
7.52
RADCOM
7.53
Radisys Corporation
7.54
Reverb Networks
7.55
Rohde & Schwarz
7.56
Rorotika
7.57
Samsung Electronics
7.58
SEDICOM
7.59
Siklu Communication
7.60
SpiderCloud Wireless
7.61
Tarana Wireless
7.62
Tektronix Communications
7.63
TEOCO
7.64
Theta Networks
7.65
TI (Texas Instruments)
7.66
TTG International
7.67
Tulinx
7.68
Vasona Networks
7.69
Viavi Solutions
7.70
WebRadar
7.71
XCellAir
7.72
ZTE
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8
Chapter 8: Market Analysis & Forecasts
8.1
SON & Mobile Network Optimization Revenue
8.2
SON Revenue
8.3
SON Revenue by Network Segment
8.3.1
SON in RAN
8.3.2
SON in Mobile Core
8.3.3
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 & Beyond
8.5.1
2G & 3G SON
8.5.2
4G & Beyond 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
8.15
Top Country Markets
8.15.1
Australia
8.15.2
Brazil
8.15.3
Canada
8.15.4
China
8.15.5
France
8.15.6
Germany
8.15.7
India
8.15.8
Italy
8.15.9
Japan
8.15.10
Russia
8.15.11
South Korea
8.15.12
Spain
8.15.13
Taiwan
8.15.14
UK
8.15.15
USA
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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, Predictive Analytics & SON
9.4
Optimizing M2M & IoT Services
9.5
SON for NFV & SDN: The Push from Mobile Operators
9.6
Moving Towards Mobile Core and Transport Networks
9.7
Assessing the Impact of SON on Optimization & Field Engineers
9.8
SON Associated OpEx Savings: The Numbers
9.9
What SON Capabilities Will 5G Networks Entail?
9.10
The C-SON Versus D-SON Debate
9.11
Strategic Recommendations
9.11.1
SON & Conventional Mobile Network Optimization Solution Providers
9.11.2
Wireless Infrastructure OEMs
9.11.3
Mobile Operators
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Companies Mentioned: 
  1. 3GPP (Third Generation Partnership Project)
  2. Accedian Networks
  3. Accuver
  4. Actix
  5. Aepona
  6. Aexio
  7. AIRCOM International
  8. AirHop Communications
  9. Airspan Networks
  10. Alcatel-Lucent
  11. Amdocs
  12. Anite
  13. Arcadyan
  14. Argela
  15. Aricent
  16. Arieso
  17. ARItel
  18. Ascom
  19. Astellia
  20. AT&T Mobility
  21. ATDI
  22. Avago Technologies
  23. Avvasi
  24. Beeline Kazakhstan
  25. BLiNQ Networks
  26. Broadcom Corporation
  27. Bytemobile
  28. Cavium
  29. CBNL (Cambridge Broadband Networks Limited)
  30. Celcite
  31. CellMining
  32. Cellwize
  33. Celtro Communications
  34. CENTRI
  35. Cisco Systems
  36. Citrix Systems
  37. Comarch
  38. CommAgility
  39. Commsquare
  40. Coriant
  41. Datang Group
  42. Datang Mobile
  43. ECE (European Communications Engineering)
  44. Eden Rock Communications
  45. Ericsson
  46. ETRI (Electronics and Telecommunications Research Institute)
  47. Flash Networks
  48. Forsk
  49. Freescale Semiconductor
  50. Fujitsu
  51. Globe Telecom
  52. Guavus
  53. Hitachi
  54. Huawei
  55. InfoVista
  56. Ingenia Telecom
  57. Intel Corporation
  58. InterDigital
  59. Intucell Systems
  60. ip.access
  61. JDSU
  62. KDDI
  63. Lavastorm
  64. Lemko Corporation
  65. Mentum
  66. MIMOon
  67. Mobilicity
  68. Mobixell
  69. NEC Corporation
  70. NetScout Systems
  71. Newfield Wireless
  72. NGNM (Next Generation Mobile Networks) Alliance
  73. Nokia Networks
  74. NXP Semiconductors
  75. Optimi
  76. Optulink
  77. P.I.Works
  78. Plano Engineering
  79. Qualcomm
  80. RADCOM
  81. Radisys Corporation
  82. Reverb Networks
  83. Rogers Communications
  84. Rohde & Schwarz
  85. Rorotika
  86. R-TRON
  87. Samsung
  88. Schema
  89. SEDICOM
  90. Siklu Communication
  91. Singtel (Singapore Telecommunications)
  92. SK Telecom
  93. SpiderCloud Wireless
  94. Symena
  95. Tarana Wireless
  96. Tektronix Communications
  97. 罢别濒别蹿贸苍颈肠补
  98. Tellabs
  99. TEOCO
  100. Teradata
  101. Theta Networks
  102. TI (Texas Instruments)
  103. TIM Brasil
  104. Trendium
  105. TTG International
  106. Tulinx
  107. Ubiquisys
  108. Vasona Networks
  109. Viavi Solutions
  110. WebRadar
  111. Xceed Technologies
  112. XCellAir
  113. ZTE
  114. 听
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