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

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ReportLinker Find Industry reports, Company profiles and Market Statistics >> Get this Report Now by email! The Self-Organizing Networks (SON) Ecosystem: 2014 - 2020 Published on March 2014 Report Summary 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: - 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: - Conventional mobile network planning & optimization The Self-Organizing Networks (SON) Ecosystem: 2014 - 2020 (From Issuu) Page 1/25

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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 complexit...

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

Page 1: The Self-Organizing Networks (SON) Ecosystem: 2014 - 2020

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

Published on March 2014

Report Summary

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:

- 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:

- Conventional mobile network planning & optimization

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- 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'

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

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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

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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

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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

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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

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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

Companies Mentioned

21 Vianet Group

2K Telecom

3 Austria

3 Denmark

3 HK

3 Ireland

3 Italia

3 Sweden

365 Media

3Roam

4G Americas

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4ipnet

6WIND

A1 Telekom

Ablaze

Accedian

Accedian Networks

Accelleran

Accuver

Actelis

Actix

Adams NetWorks

ADLINK

ADTRAN

ADVA

Advantech

Aero2

Aerohive

Aeronet

Aexio

Aircel

Aircell

AIRCOM International

AirHop Communications

Airspan Networks

Airtel Nigeria

Airvana

AIS/DPC Thailand

Al Madar

Alaska Communications

Albis Technologies

Alcatel-Lucent

Alfa

Algar Telecom (CTBC)

Algerie Telecom

Alpha Networks

Altel

Altera

Alvarion

Amdocs

Andorra Telecom

Andrew

Antares Group

Antel

Anvaya Networks

Aptilo

Aqiva Wireless

Aquafon

Arcadyan

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Argela

ARIB (Association of Radio Industries and Businesses, Japan)

Aricent

Arieso

ARItel

Armentel

Aruba Networks

Ascom

Asiaspace

Askey

ASOCS

Astellia

AT&T Mobility

ATDI

Athena Wireless Communications

ATIS (Alliance for Telecommunications Industry Solutions, U.S.)

Atrica

Avanti

Avea

Aviat Networks

Avvasi

Axell Wireless

Axerra Networks

Axis Teknologies

Azercell

Azerfon

b'lite

Babilon Mobile

Bakcell

Bakrie Telecom

Batelco

Bayan Telecommunications

BayRICS

Beeline

Beeline Lao

BelCel

Belgacom / Proximus

Bell Mobility

BendBroadband

BeST (Life)

BH Telecom

Bharti Airtel

Bhutan Telecom

Big Switch Networks

BigAir

BLiNQ Networks

Bluegrass Cellular

Blueline

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BluWan

Bollore Telecom

Bouygues Telecom

Brazil Army

Brazil Sao Paulo Military Police

BridgeWave Communications

Broadcom

Brocade

Browan

BSNL

BT

BTC

BTI Systems

BTI Wireless

BTL

BUCD

Bulgaria Vivacom

Bytemobile

C Spire Wireless

C&S

Cable and Wireless

Cambium Networks

Canoga Perkins

Carolina West Wireless

Carrier Access Corporation

Cavium

CBL Bahamas

CBNL (Cambridge Broadband Networks Limited)

CCI (Communication Components Inc.)

CCS

CCSA (China Communications Standards Association, China)

CDMA Development Group

Ceclcom Axiata

CeedTec

Celcite

Cell C

Cellcom

CellO

Cellvine

Cellwize

Celtro

CENTRI

CenturyLink

Ceragon

Chariton Valley Comms

Charles Industries

Chat Mobility

China Mobile

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China Mobile Hong Kong

China Telecom

China Unicom

CHT

Cielo

Ciena

Cisco Systems

Citrix

City of Charlotte Council

Claro

Clear Mobitel

CNT

COAI (Cellular Operators Association of India)

Cobham

Coherent Logix

Colorado Valley

Comarch

Comba Telecom

Commnet Wireless

CommScope

Commsquare

Contela

ConteXtream

Continuous Computing

Convergence Technologies

Copper Valley Telecom

Corning

Cosmote

COTA Murcia4G

Cross Telephone

Crown Castle

CSI

CSL Limited

Custer Telephone

Cyan

Cyan

Datame

DBD

Dedicado

DeltaNode

Deutsche Telekom

Dhiraagu

Dialog Axiata LTE TDD later FDD

Dialogic

DiGi

Digicel

Digicel Fiji

Digitel

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Digitel Jamaica

Dish Network

D-Link

DNA

DoCoMo Pacific

DragonWave

DTAC ' TriNet

DTM (Datang Mobile)

Du

E Plus

eAccess

Eastlink

E-Band Communications

ECE (European Communications Engineering)

ECI Telecom

Econet Wireless

Eden Rock Communications

Edgewater

EE

EION

Elisa

EMT

Emtel

EnergyAustralia Ausgrid

EnGenius

Entel Movil

Entel PCS

Entel Peru

Enterasys

ERA/T-Mobile Poland

Ericsson

ETC

Etex Telephone Co-op

EtherReach

Ethertronics

Ethio Telecom

Ethos

Etisalat

Etisalat Misr

ETRI (Electronics and Telecommunications Research Institute)

ETSI (European Telecommunications Standards Institute)

Evolve Broadband

Exalt

ExteNet Systems

Extreme Networks

FarEasTone

FastBack Networks

Fastlink (Regional Telecom)

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Femtel

FibroLAN

Firetide

Fitel

Fjarskipti (Vodafone Iceland)

Forsk

Fortinet

FPT Telecom

Freescale Semiconductor

Fujitsu

Gemtek

Genband

Georgia Magticom

Glo Mobile

Globacom

Global Mobile

Globe

GoNet Systems

Goodman Networks

Gore

GrenTech

GSA

GSMA (GSM Association)

Guavus

Guineanet

GWT (Global Wireless Technologies)

Handlink

Hatteras

Hitachi

HP

Huahuan

Huawei

Hutchison 3

IBW International

ICE

iConnect

IDC Moldova

iDirect

IEEE (Institute of Electrical and Electronics Engineers)

IM2

Imagine Group

IMS Forum

InfoCommunication Union

InfoVista

Ingenia Telecom

InnerWireless (Acquired by Black Box)

Intel

InterDigital

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Intracom

Intucell Systems

Inwi

Iowa Statewide Interoperable Communications Board (ISICSB)

ip.access

IPITEK

IPV6 Forum

Islandcom

IT&E Guam

JDSU

Juni

Juniper Networks

Kcell

KDDI

Kentrox

Kordia

KPN

KPN Base

KPU (Alaska)

KT

KT Corp Rwanda

Lanka Bell

Lantiq

Lattelecom

Lavastorm

Leap Wireless/Cricket

Lemko

LG U+

LightPoint Communications

Lightsquared

LIME

Linkem

LMT

LSI

LTC

M/A-COM Technology Solutions

M1

Manx Telecom

Mascom Wireless

Massnet

MAX Telecom

Maxim Integrated

Maxis

MaxyTel

Megafon

Menatelecom

Mentum

Meru Networks

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Mesaplexx

Meteor

Microwave Networks

Mid-Rivers Communications

Milmex

mimoOn

Mindspeed Technologies

MiSpot

Mobile Norway/Tele2

MobileAccess

Mobily

Mobinil

Mobistar

Mobitel

Moldcell

Monaco Telecom

Mongolia Telecom

Mosaic Telecom

Motorola Solutions

Movicel

Movilmax

Movilnet

Movistar

MRV Communications

MTA

MTC

MTC Touch

M-Tel

MTN

MTN Uganda

MTNL

MTPCS

MTS

MTS Allstream

MTS Belarus

MTS Ukraine

Myanmar P & T

Nawras

NBN Co.

Ncell

NEC

Neo-Sky

Neotel

Nepal Telecom

NetGear

NetLogic Microsystems

Netronome

Newfield Wireless

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NewNet

Nexius

NGMN (Next Generation Mobile Networks)

NITA

Node-H

Nomadix

Nomor Research

Nortel Networks

NorthwestCell

Nova

NSN (Nokia Solutions & Networks)

nTelos

nTelos Wireless

NTT DoCoMo

Nuage Networks (Alcatel-Lucent)

O2 Secure Wireless

Octasic

Oi

Omantel

Omnitel

On Telecomunicacoes

ONE

Ooredoo

Open Mobile

Optimi

Optimus

Optiway

Optulink

Optus

Orange Armenia

Orange Austria

Orange Dominicana

Orange France

Orange Liechtenstein

Orange Luxembourg

Orange Mauritius

Orange Moldova

Orange Romania

Orange Slovak Republic

Orange Spain

Orange Switzerland

Orange Uganda

Orckit Corrigent

Osnova Telecom

Overture

P&T

P.I.Works

P1 Networks

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P4 (Play)

Pandetel

Panhandle Telephone Co-op

PCCW

Peoples Telephone Co-op

Personal

PicoChip

Pioneer Cellular

Plano Engineering

Plexxi

Polkomtel Plus

Positron-Aktino

Powerwave Technologies

Proxim

PTK Centertel (Orange)

Public Service Wireless

Public Wireless

PureWave Networks

PVT

Qualcomm

Quortus

R (Spain)

RAD Data Systems

RADCOM

Radisys

RADWIN

Rakon

RCS & RDS

Redline Communications

REDtone

Reliance

Reverb Networks

RF Window

RFNet

RFS (Radio Frequency Systems)

Rogers Wireless

Rohde & Schwarz

Rorotika

Rostelecom

Ro-Timak Technology

Ruckus Wireless

RusViet Telecom

S and R Communications

S&T Telephone Cooperative

Safaricom

Sagebrush Cellular (Nemont)

Sagem

Sagemcom

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SAI Technology

Saima Telecom

Samsung

Sasktel

Sazz

Schema

SEDICOM

SerComm

SFR

SGRITA

Shentel

Shyam Networks

Si.mobil

SIAE Microelectronics

Siklu

Siminn

SingTel

SK Telecom

SK Telesys

Sky Brazil

Small Cell Forum

Smart Communications

Smartone

SMARTS

Smile

Smoltelecom

Softbank

Softbank Mobile

SOLiD Technologies

Spectranet

SpeedConnect

SpiderCloud Wireless

Sprint

Sprint Nextel

Sprocket Wireless

SRT Communications

SSTL

Star Microwave

Starcomms

StarHub

STC

Strata Networks

Strix Systems

Sub10 Systems

Sunrise Communications

Surfline Communications

SWIFT Networks

Swisscom

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Sycamore

Symena

Syringa Wireless

T Mobile

Tango

Tango Networks

Taqua

Tarana Wireless

Tata Elxsi

TCCA (TETRA and Critical Communications Association)

TDC

TD-Forum

TDIA (TD Industry Alliance)

TE Connectivity (Tyco Electronics Connectivity)

Tecom

TEKTELIC

Tektronix Communications

Telcel

Telco Systems

Tele2

Tele2 Kazakhstan

Tele2 Sweden

Telecom Italia Mobile (TIM)

Telecom Malaysia

Telecom New Zealand

Telefonica Movistar

Telefonica O2

Telefonica O2 Ireland

Telefonica O2 UK

Telefonica Peru

Telefonica Spain

Telekom Srpske

Telenet Belgium

Telenor Denmark

Telenor Hungary

Telenor Montenegro

Telenor Norway

Telenor Sweden

Telesis

TeliaSonera

TeliaSonera Norway

TeliaSonera Sweden

Telkom Mobile (8ta)

Telkomsel Indonesia

Tellabs

Telrad

Telstra

Telus

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TEOCO

Teradata

Texas Energy Network

Texas Instruments

TFL

Theta Networks

Thomson

T-Hrvatski Telekom

Thumb Cellular

Tigo

Tikona

TIM Brasil

TM Forum (TeleManagement Forum)

TMC

TMN (Portugal Telecom)

T-Mobile Czech Republic

T-Mobile Hungary

T-Mobile Macedonia

T-Mobile Netherlands

T-Mobile Puerto Rico

T-Mobile Slovensko

T-Mobile USA

TN Mobile

TOT Thailand

TPG Internet

TP-Link

TRaC Global

Trango Systems

Transmode

Tranzeo

Trendium

Triatel

Tricom

Tropos

True Move

TSKL

TTA (Telecommunications Technology Association, Korea)

TTC (Telecommunication Technology Committee, Japan)

TTG International

TTK

Tulinx

Tunisiana

Turkcell

U Mobile

UbeeAirWalk

Ubidyne GmBH

Ubiquisys

Ubiquiti Networks

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u-blox

UCell

UK Broadband

Ulusnet

Umniah

UMTS Forum

Une-EPM

United Wireless

Unitel

US Cellular

Vainakh Telecom

VDC (VNPT)

Vector

Velatel

Velatel-Aerostrong

Verizon Wireless

Videocon

Videotron

Viettel

Vimpelcom

VIP mobile

VIPNet

Visafone Communications

Viva

Vivacell-MTS

Vivato

Vivo

VMWare

Vodacom

Vodacom Tanzania

Vodafone

Vodafone Australia

Vodafone Czech Republic

Vodafone Egypt

Vodafone Fiji

Vodafone Greece

Vodafone Ireland

Vodafone Italy

Vodafone New Zealand

Vodafone Portugal

Vodafone Qatar

Vodafone Romania

Vodafone Spain

Vodafone UK

Vox

VTel Wireless

Vubiq

Wataniya

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Wataniya Telecom

WBS (iBurst)

WebRadar

West Central Wireless

Wi-Ex

Wilson Electronics

Wind

Wind Mobile

WNC (Wistron NeWeb Corp.)

Woosh

Xceed Technologies

Xilinx

XL Axiata

Xplornet

Yoigo

Yota

YTL Communications Yes

Zain

Zain Jordan

Zain Saudi

Zamtel

Zhone

Ziggo

Zinwave

Zoda Fones

ZTE

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