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@BigDataExpo Authors: Flint Brenton, Bob Gourley, Liz McMillan, Elizabeth White, Deep Bhattacharjee

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SON & Mobile Network Optimization Market - $3 Billion Revenue by 2016 Forecasts offers The Self-Organizing Networks (SON) Ecosystem: 2014 - 2020 research report to its store. Amid growing demands for mobile broadband connectivity, wireless carriers are keen to capitalize on SON to minimize rollout delays and opera

DALLAS, March 29, 2014 /PRNewswire-iReach/ -- 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.

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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. Complet report available @ 709 Companies are listed in the report.

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.

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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
  • The 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
  • The 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:

  • 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

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Key Questions Answered:

  • 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?

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