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’s services, improving the OpEx to revenue ratio.
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 small cell deployments.
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. In addition, Wi-Fi access point OEMs are beginning to integrate SON features such as plug-and-play deployment, autonomous performance optimization, self-healing and proactive defense against unauthorized access.
Despite challenges relating to implementation complexities and multi-vendor interoperability, SON revenue is expected to grow to more than $5 Billion by the end of 2020, exceeding conventional mobile network optimization revenue by a significant margin. Furthermore, the SON ecosystem is increasingly witnessing convergence with other technological innovations such as Big Data, predictive analytics and DPI (Deep Packet Inspection).
The “SON (Self-Organizing Networks) Ecosystem: 2016 – 2030 – Opportunities, Challenges, Strategies & Forecasts” 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 10 SON submarkets, 6 regions and 15 countries from 2016 through to 2030.
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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:
– 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
– Future roadmap of the SON ecosystem
– Company profiles and strategies of over 120 SON ecosystem players
– OpEx and CapEx saving analysis of SON
– Wireless network infrastructure spending, traffic projections and value chain
– Convergence of SON with Big Data, predictive analytics and DPI
– Strategic recommendations for SON solution providers, wireless infrastructure OEMs and mobile operators
– Market analysis and forecasts from 2016 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
– Macrocell RAN
– HetNet RAN
– Mobile Core
– Mobile Backhaul & Fronthaul
SON Architecture Submarkets
– C-SON (Centralized SON)
– D-SON (Distributed SON)
SON Access Network Technology Submarkets
– 2G & 3G
– LTE
– Wi-Fi
– 5G
Regional Markets
– Asia Pacific
– Eastern Europe
– Latin & Central America
– Middle East & Africa
– North America
– Western Europe
Country Markets
– Australia
– Brazil
– Canada
– China
– France
– Germany
– India
– Italy
– Japan
– Russia
– South Korea
– Spain
– Taiwan
– UK
– USA
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?
– How can SON ease the deployment of unlicensed LTE small cells?
– What SON capabilities will 5G networks entail?
– What is the outlook for C-SON and D-SON adoption?
– How will SON investments compare with those on traditional mobile network optimization?
– What opportunities exist for SON in mobile core and transport networks?
– How will SON use cases evolve overtime in 3GPP releases?
– Which regions will see the highest number of SON investments?
– How much will mobile operators invest in SON solutions?
– What is the outlook for SON associated OpEx savings by region?
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 $5 Billion by the end of 2020, exceeding conventional mobile network optimization revenue by a significant margin.
– Mobile operators have reported up to a 50% reduction in dropped calls and over 20% higher data rates with SON implementation. Besides common network optimization use cases, operators are also capitalizing on SON platforms to address critical business objectives such as refarming 2G/3G spectrum for LTE networks.
– In a bid to differentiate their products, Wi-Fi access point OEMs are beginning to integrate SON features such as plug-and-play deployment, autonomous performance optimization, self-healing and proactive defense against unauthorized access.
– 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 continuing to acquire smaller established C-SON players to accelerate their entry path into the C-SON market.
Table Of Contents – Major Key Points
Chapter 1: Introduction
Executive Summary
Topics Covered
Forecast Segmentation
Key Questions Answered
Key Findings
Methodology
Target Audience
Companies & Organizations Mentioned
Chapter 2: SON & Mobile Network Optimization Ecosystem
Conventional Mobile Network Optimization
Network Planning
Measurement Collection: Drive Tests, Probes and End User Data
Post-Processing, Optimization & Policy Enforcement
The SON (Self-Organizing Network) Concept
What is SON?
The Need for SON
Functional Areas of SON
Self-Configuration
Self-Optimization
Self-Healing
Market Drivers for SON Adoption
Continued Wireless Network Infrastructure Investments
Optimization in Multi-RAN & HetNet Environments
OpEx & CapEx Reduction: The Cost Saving Potential
Improving Subscriber Experience and Churn Reduction
Power Savings
Enabling Small Cell Deployments
Traffic Management
Market Barriers for SON Adoption
Complexity of Implementation
Reorganization & Changes to Standard Engineering Procedures
Lack of Trust in Automation
Lack of Operator Control: Proprietary SON Algorithms
Coordination between Distributed and Centralized SON
Network Security Concerns: New Interfaces and Lack of Monitoring
Chapter 3: SON Technology, Use Cases & Implementation Architectures
Where Does SON Sit Within a Mobile Network?
RAN
Mobile Core
Mobile Backhaul & Fronthaul
Device-Assisted SON
SON Architecture
C-SON (Centralized SON)
D-SON (Distributed SON)
H-SON (Hybrid SON)
SON Use-Cases
Self-Configuration of Network Elements
Automatic Connectivity Management
Self-Testing of Network Elements
Self-Recovery of Network Elements/Software
Self-Healing of Board Faults
Automatic Inventory
ANR (Automatic Neighbor Relations)
Continue…….
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