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市場調査レポート

3G・LTE以降における自己組織ネットワーク(SON)の課題・市場機会

Self-Organizing Networks (SON) Challenges and Market Opportunities for 3G, LTE, and Beyond, Fourth Edition

発行 Mind Commerce Publishing LLC 商品コード 297168
出版日 ページ情報 英文 219 Pages
納期: 即日から翌営業日
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本日の銀行送金レート: 1USD=107.50円で換算しております。
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3G・LTE以降における自己組織ネットワーク(SON)の課題・市場機会 Self-Organizing Networks (SON) Challenges and Market Opportunities for 3G, LTE, and Beyond, Fourth Edition
出版日: 2014年03月06日 ページ情報: 英文 219 Pages
概要

モバイルネットワークオペレーターは、自身の大規模なネットワークを効率的に管理するため、さらなる自動化を探求しています。自己組織ネットワーク(SON)の役割は高効率を実現し、いくつかのケースではセルラーネットワークを微調整するプログラミング手段となっています。

当レポートでは、自己組織ネットワーク(SON)市場について取り上げ、SONの機能、ベンダー、およびソリューションを評価しており、3G・LTE関連のSON機能の分析と導入・運営のメリットの評価、4G以降の将来のSONに関する議論、および全体的なOSS/BSS収益の予測などをまとめ、概略以下の構成でお届けいたします。

第1章 イントロダクション

第2章 SON技術の概要

  • 異種ネットワークに向かう進化
  • 3GPPリリースにおけるSON
  • 自己組織ネットワークの概要
  • 自己組織ネットワークのメリット

第3章 SONの利用例・現在の市況

  • SONアプリケーション
  • 設置段階
  • LTE SONリリース
  • ANR(Automatic Neighbor Relation)
  • SONにおけるロードバランシング
  • MRO(Mobility Robustness Optimization)
  • SONにおける分散型クラスタリング
  • 使用可能な利用例
  • 都市の自己組織ネットワーク

第4章 アンテナパラメーターおよびアンテナチルトのコスト削減

  • 電気チルト
  • 機械チルト
  • SON vs. SON関連の技術/ソリューション
  • 設置アンテナチルトとそのパラメーター
  • アンテナチルトの機能およびROI

第5章 SONのビジネス価値

  • NGMNの利用例
  • オペレーターのメリット
  • オペレーターにとってのSONの価値
  • LTEを展開するオペレーターへの提言

第6章 SONベンダーの情勢

  • 自動構成・SON
  • Optimi
  • Ericsson
  • Actix
  • Motorola
  • Huawei
  • Nokia-Siemens Networks
  • AirHop
  • Qualcomm UltraSON
  • Cisco
  • Xceed Technologies
  • AIRCOM
  • Celcite (Amdocs)

第7章 SONプロバイダーの比較分析

  • SONプロバイダーの比較:クライアントフィードバック別
  • SONプロバイダーの比較:セットアップコスト別
  • SON新興企業
  • ベンダーの5カ年予測
  • RAN最適化ベンダーの分析

第8章 SON・RON最適化市場

  • SON市場の促進因子
  • 主な市場動向
  • 市場アップデート
  • コグニティブ無線ネットワーク(CRN)・SON
  • 自己組織ネットワーク・RAN最適化市場
  • LTE RAN装置市場

第9章 結論・提言

  • キャリアSONの導入
  • その他の目的でのSON利用

第10章 付録

図表リスト

目次

Mobile network operators are looking for more automation in order to efficiently manage their large networks, which consist of thousands of base stations with hundreds of settings each. The role of Self-organizing Networks (SON) is to enable efficient, and in some cases programmatic means of fine tuning cellular networks.

SON can fix fundamental problems (i.e. the tire is out of alignment analogy), such as poor coverage and/or dropped calls in an area and it can also be used for short-term, real-time issues (and then potentially be put back the way the network was in the first place. For example, the network may need optimization locally for a specific event such as a sporting event or live show/concert. In all cases, SON is designed to support wireless carriers desire to provide a multitude of different services with high quality of experience for the end-user.

Approximately 80-85% of global providers focus on SON only in the 3G portion of their networks today. This is because they want to first optimize what is stable and most of the network, while they work out other issues on 4G. The ultimate implementation of SON in 4G networks will bring many advantages. For example, 4G has something called "Reserved Quality" (talked about on 3G, but not really there) as a means of managing Quality of Service (QoS) and Quality of Experience (QoE). This represents a benefit of SON on LTE in terms of optimizing network to support the QoS/QoE metrics. Leading vendors, such as Amdocs (who acquired Celcite) recognize this and are building solutions for improving customer experience.

This research evaluates SON capabilities, vendors, and solutions. It analyzes the function of SON relative to 3G and LTE and evaluates the benefits of deployment and operation. The report also discusses the future of SON beyond 4G. This research includes a forecast for overall OSS/BSS revenue.

Report Benefits:

  • SON forecasts and regional outlook
  • SON case studies and future outlook
  • Understand SON technology and solutions
  • Identify the benefits of SON in 4G networks
  • Understand network optimization alternatives
  • Recognize SON benefits including CapEx reduction
  • Identify SON vendors, offerings, and their market positions
  • Identify the alternative uses for SON including data analytics
  • Understand SON deployment, operation, and related solutions

Companies in Report:

  • Actix
  • AIRCOM
  • AirHop
  • Alcatel Lucent
  • Aricent
  • Arieso
  • Ascom
  • Astellia
  • AT&T
  • Axis
  • Bytemobile
  • Celcite (Amdocs)
  • Celtro
  • Cisco
  • Commsquare
  • EarthComm
  • Ericsson
  • Huawei
  • Intucell
  • Lightsequared
  • Mentum
  • Motorola
  • NEC
  • Newfield Wireless
  • Nokia Siemens Networks
  • Optimi
  • P.I.Works
  • Plano Engineering
  • Qualcomm UltraSOn
  • Reverb
  • Schema
  • Symena
  • Telstra
  • Theta Networks
  • T-Mobile
  • TTG International
  • Tulinx
  • Ubiquisys
  • Vector
  • Verizon
  • Vodafone
  • Xceed

Table of Contents

1. Introduction

  • 1.1. Executive Summary
  • 1.2. Topics Covered
  • 1.3. Key Questions Answered
  • 1.4. Target Audience
  • 1.5. Companies Mentioned

2. SON Technology Overview

  • 2.1. The Evolution towards Heterogeneous Networks
  • 2.2. SON in 3GPP Release 11
    • 2.2.1. Releases 8, 9 and 10 Standardization
    • 2.2.2. 3GPP Release 8
    • 2.2.3. 3GPP Release 9
    • 2.2.4. 3GPP release 10
    • 2.2.5. 3GPP Release 11
  • 2.3. Self-Organizing Networks Overview
  • 2.4. Self-Organizing Networks Benefits
    • 2.4.1. Network Automation
    • 2.4.2. Energy Saving
    • 2.4.3. Lower Equipment Costs
    • 2.4.4. Distributed/Self-organizing (DSO)
    • 2.4.5. Cooperative Relaying (CR) in SON
    • 2.4.6. Feedback Overhead in SON
    • 2.4.7. Codebook-based Pre-coding SON
    • 2.4.8. Feedback Delay in SON

3. SON Use Cases and Current Market Status

  • 3.1. SON Applications
    • 3.1.1. Self-Configuration
    • 3.1.2. Self-Optimization
    • 3.1.3. Self-Healing
    • 3.1.4. Problems with Self-Healing
  • 3.2. Installing Phases
    • 3.2.1. Centralized SON
    • 3.2.2. Distrusted SON
    • 3.2.3. Localized SON
    • 3.2.4. Hybrid SON
  • 3.3. LTE SON Releases
  • 3.4. Automatic Neighbor Relation (ANR)
    • 3.4.1. Installing ANR
  • 3.5. Load Balancing in SON
  • 3.6. Mobility Robustness Optimization (MRO)
  • 3.7. Distributed Clustering in SON
  • 3.8. Operational Use Cases
    • 3.8.1. ICIC Enhancement
  • 3.9. Urban Self-Organizing Networks
    • 3.9.1. Home/Residential Deployments:
    • 3.9.2. Enterprise Deployments:
    • 3.9.3. Metro and Public Space Deployments:
    • 3.9.4. Rural Deployments:
    • 3.9.5. SON based on Small Cell Deployments

4. Antenna Parameters and Antenna Tilt Cost Reduction

  • 4.1. Electrical Tilt
  • 4.2. Mechanical Tilt
  • 4.3. SON vs. SON-related Technologies/Solutions
  • 4.4. Installing Antenna Tilt and its Parameters
  • 4.5. Features and ROI of the Antenna Tilts
    • 4.5.1. Overcoming Performance Issues in a Specific DAS Coverage Area
    • 4.5.2. Energy Saving

5. SON Business Value

  • 5.1. NGMN Use Case
  • 5.2. Operators Benefits
  • 5.3. Values of the SON to Operators
    • 5.3.1. Economic Benefits
    • 5.3.2. SON Implementation Expenditures (IMPEX)
    • 5.3.3. SON Capital Expenditures (CAPEX)
    • 5.3.4. SON Operational Expenditures (OPEX)
    • 5.3.5. Smarter Self Organizing Networks
  • 5.4. Recommendations for Operators to Deploy LTE

6. SON Vendor Landscape

  • 6.1. Auto Configuration and SON
  • 6.2. Optimi Solutions
    • 6.2.1. Clients' feedback on the Solution
    • 6.2.2. SWOT Analysis for Optimi
    • 6.2.3. Optimi Multi-Technology Self-Organizing Networks (SON for the 3G)
  • 6.3. Ericsson SON Solution
    • 6.3.1. Advanced SON from Ericsson
  • 6.4. Actix
    • 6.4.1. SON by Actix
    • 6.4.2. Actix SWOT
    • 6.4.3. Client's Feedback on Actix SON Solution
    • 6.4.4. NEC and Actix SON
  • 6.5. Motorola
    • 6.5.1. Motorola SWOT
    • 6.5.2. Motorola SON services
    • 6.5.3. Features of Motorola SON
  • 6.6. Huawei SON Solution
    • 6.6.1. Phase one: Planning
    • 6.6.2. Phase Two: Deployment
    • 6.6.3. Phase Three: Optimization
    • 6.6.4. Phase Four: Maintenance
    • 6.6.5. Huawei SON Analysis
  • 6.7. Nokia-Siemens Networks SON Solution
    • 6.7.1. NSN SON Analysis
    • 6.7.2. Intelligent Self Organizing Networks (iSON) from NSN
  • 6.8. AirHop
    • 6.8.1. Airhop SON Solution Analysis
    • 6.8.2. Client's Feedback on Airhop SON Solutions
  • 6.9. Qualcomm UltraSON
    • 6.9.1. Qualcomm UltraSON Solution Analysis
  • 6.10. Cisco
    • 6.10.1. Cisco Intucell SON Analysis
  • 6.11. Xceed Technologies
    • 6.11.1. Xceed Xynergy SON Analysis
  • 6.12. AIRCOM
    • 6.12.1. AIRCOM I-VIEW SON Solution
  • 6.13. Celcite (Amdocs)
    • 6.13.1. Celcite Value Proposition

7. SON Provider Comparative Analysis

  • 7.1. Comparison between SON Providers by Clients Feedback
  • 7.2. Comparison between SON Provider by Setup Cost
  • 7.3. SON Start-ups
    • 7.3.1. Who is Dominating the Market and Why
    • 7.3.2. The Future of LTE, 5G and Beyond
  • 7.4. Where Vendors will be in Five Years
  • 7.5. RAN Optimization Vendors Analysis

8. SON and RAN Optimization Market 2014-2019

  • 8.1. Factors Driving the SON Market
  • 8.2. Key Market Trends
  • 8.3. 2014 Market Update
  • 8.4. Cognitive Radio Network (CRN) and SON
  • 8.5. Self-Organizing Networks and RAN Optimization Market 2014-2019
  • 8.6. LTE RAN Equipment Market 2014-2019

9. Conclusions and Recommendations

  • 9.1. Carrier SON Deployments
    • 9.1.1. Mobile Optimization
    • 9.1.2. Optimization Solutions
  • 9.2. Leveraging SON for other Purposes
    • 9.2.1. SON, Big Data, and Predictive Analytics
    • 9.2.2. SON and the Two-sided Business Model (Asymmetric Business Model)
    • 9.2.3. Wireless Carrier Offerings

10. APPENDIX

  • 10.1. Long Term Evolution Market and Technology Overview
  • 10.2. LTE Market Overview
    • 10.2.1. Market Drivers
    • 10.2.2. The Shift from Voice to Data Centric Services
    • 10.2.3. The Demand for Higher Data ARPUs
    • 10.2.4. Capacity Management and OPEX Reduction
    • 10.2.5. Lack of Fixed Broadband in Low Density Areas
    • 10.2.6. Vendor Commitments
  • 10.3. Market Barriers
    • 10.3.1. Spectrum Congestion
    • 10.3.2. High Investments for Early Adopters
    • 10.3.3. Consumer Device Challenges
    • 10.3.4. Broadband Pricing and International Roaming
  • 10.4. LTE Technology Overview
    • 10.4.1. Technology Overview
    • 10.4.2. Performance Metrics
    • 10.4.3. LTE Advanced
    • 10.4.4. Integration with Deployed Networks
  • 10.5. Next Generation Network (NGN) OSS/BSS
    • 10.5.1. NGN OSS Overview
    • 10.5.2. Drivers of NGN
    • 10.5.3. Telecom Operator and Vendor Interests
    • 10.5.4. Improvement in Access Technologies
    • 10.5.5. Reduced Vendor Dependency
    • 10.5.6. Operational Challenges
    • 10.5.7. Integration of Multiple Private Networks and Application into Public Networks
    • 10.5.8. Quality of Service (QoS)
    • 10.5.9. National Security and Competitive Policies
  • 10.6. NGN OSS/BSS: Components, IMS Implications and Frameworks
    • 10.6.1. Network Planning and Engineering
    • 10.6.2. Fault Management
    • 10.6.3. Performance Management
    • 10.6.4. Provisioning and Service Activation
    • 10.6.5. Inventory Management
    • 10.6.6. Billing and Customer Care
    • 10.6.7. Mediation
    • 10.6.8. Revenue Assurance
    • 10.6.9. Challenges for OSS and BSS
  • 10.7. OSS Challenges
    • 10.7.1. Stakeholder Apprehensions
    • 10.7.2. Framework to Integrate Customization Demands
    • 10.7.3. Smooth Transition from Existing OSS Frameworks
    • 10.7.4. Multi-vendor Coordination
    • 10.7.5. BSS Challenges

List of Figures

  • Figure 1: HetNet Network Topology
  • Figure 2: SON Use Cases
  • Figure 3: LTE SON Releases
  • Figure 4: Comparisons between Centralized, Distributed and Localized SON
  • Figure 5: SON Operational Use Cases
  • Figure 6: Self Organizing Networks (SON) Concept
  • Figure 7: Antenna Tilt
  • Figure 8: Electrical Tilt
  • Figure 9: Mechanical Tilt
  • Figure 10: Operational Efficiency for SON
  • Figure 11: Fundamental SON Capabilities
  • Figure 10: Strategic Requirements and Business Drivers for SON
  • Figure 11: Types of SON Architectures
  • Figure 14: Qualcomm UltraSON Solution
  • Figure 15: USA Frequency Allocation Chart
  • Figure 14: SON and CRN
  • Figure 17: Global SON and RAN Optimization Market 2014-2019
  • Figure 18: Global LTE RAN Equipment Spending 2014-2019

List of Tables

  • Table 1: SON Vendor Rankings
  • Table 2: SON Cost Comparison
  • Table 3: SON Optimization Market Revenue 2014 - 2019
  • Table 4: LTE RAN Equipment Market Revenue 2014 - 2019
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