The Report The Self-Organizing Networks (SON) Ecosystem: 2014 - 2020 provides information on pricing, market analysis, shares, forecast, and company profiles for key industry participants. - MarketResearchReports.biz

Albany, NY -- (SBWire) -- 01/30/2015 --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.

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).

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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.

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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

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