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5G/Open RAN 时代的 SON（自组织网络）：2022-2030 - 机遇、挑战、战略、预测
市场调查报告书
商品编码
1168241

5G/Open RAN 时代的 SON（自组织网络）：2022-2030 - 机遇、挑战、战略、预测

SON (Self-Organizing Networks) in the 5G & Open RAN Era: 2022 - 2030 - Opportunities, Challenges, Strategies & Forecasts
出版日期: | 出版商: SNS Telecom & IT | 英文 443 Pages; 60 Tables & Figures | 商品交期: 最快1-2个工作天内

价格

SON（自组织网络）技术最大限度地降低了移动网络生命週期成本，从部署期间手动配置网络元素到运营期间的动态优化和故障排除。 除了改善网络性能和客户体验外，SON 还可以显着降低移动运营商的服务成本，提高运营成本与收入的比率，并推迟可避免的资本支出。

SON 的早期采用者体验到更快的 5G NR 和 LTE RAN（无线电接入网络）推出时间、更容易的网络升级、更少的掉线、更高的呼叫建立成功率以及改善的最终用户体验。我们已经看到了许多好处，例如随着吞吐量的增加、特殊事件期间拥堵的减少、用户满意度和忠诚度的提高、运营效率（例如能源和成本的节省）以及无线电工程师从重复性手工工作中解脱出来。

SON 最初是作为一种操作方法开发的，用于简化和自动化蜂窝 RAN 的部署和优化。进一步增强自学习等新功能的集成，并将 SON 的范围从 RAN 扩展到移动核心和传输网段，对于解决端到端网络切片等 5G 需求至关重要。它配备了一个功能，成为

另外，移动通信行业正在向开放接口、虚拟化、软件驱动组网方向发展，SON生态系统正在取代传统的D-SON（分布式SON）和C-SON（集中式SON）。我们正逐步从一种方法转向基于开放标准的组件，这些组件支持 RAN 的可编程性以实现高级自动化和智能控制。

创新的 Open RAN 和 vRAN（虚拟化 RAN）架构的普及导致基于开放标准的 RIC（RAN 智能控制器）被引入传统的利基和专有产品驱动的 SON 市场。、xApp 和 rApp再次进入。 这些产品能够支持近实时 D-SON 和非实时 C-SON，以满足 RAN 自动化和优化需求。

我们估计，到 2023 年，全球在 RIC 平台、xApps 和 rApps 上的支出将达到 1.2 亿美元，随着首次实施从现场测试转向生产级部署，这一支出还会增长。 随着商业的进一步成熟，到 2025 年底，该市场预计将增长五倍，达到约 6 亿美元。 广泛的SON市场（嵌入式D-SON功能、第三方C-SON功能及相关OSS平台的授权、移动运营商自研SON功能、RAN、跨移动核心和承载领域的SON相关专业服务等）预计每年的投资将以 7% 左右的复合年增长率同期增长。

本报告分析了全球 SON（自组织网络）市场的最新趋势和未来前景，提供了 SON、体系结构生态系统、当前/未来主要用例和主要市场的技术概述。驱动和信息等信息将收集制约因素、主要用例、未来技术发展方向、主要公司概况和战略、整体市场规模和增长率（2022-2030），为行业利益相关者提供建议。

内容

第一章介绍

第2章SON和移动网络优化生态系统

  • 常规移动网络优化
    • 网络规划
    • 测量数据收集：路测、探测、最终用户数据
    • 后处理、优化和政策执行
  • SON（自组织网络）的概念
    • 什么是儿子？
    • 需要儿子
  • SON 功能区
    • 自我配置
    • 自我优化
    • 自我修復
    • 自卫
    • 自学
  • SON 价值链
    • SON，xApp/rApp，自动化专家
    • OSS &RIC 平台提供商
    • RAN/核心/传输网络设备供应商
    • 无线服务提供商
    • 最终用户
    • 其他生态系统参与者
  • 市场驱动力
    • 5G/Open RAN 时代：基础设施持续投资
    • 在復杂的多 RAN 环境中进行优化
    • 减少运营和资本支出：节省成本的潜力
    • 改善订阅者体验并减少流失
    • 节能：迈向更环保的移动网络
    • 通过交通管理缓解拥堵
    • 实现小型基站的即插即用部署
    • 私有 4G/5G 网络的扩散和渗透
  • 市场壁垒
    • 实施复杂性
    • 重组和更改标准工程程序
    • 对自动化缺乏信任
    • 独特的SON算法
    • 分布式和集中式 SON 之间的协调
    • 网络安全问题：新接口和缺乏监控

第3章SON技术、实现架构和用□□例

  • SON 在移动网络中的什么位置？
    • RAN
    • 移动核心
    • 传输（前传、中传、回传）
    • 设备辅助 SON
  • 传统 SON 架构
    • D-SON（分布式儿子）
    • C-SON（集中式 SON）
    • H-SON（混合 SON）
  • 基于开放标准的 RIC、xApps 和 rApps
    • RIC（RAN 智能控制器）
    • xApps：打开 D-SON 应用程序
    • rApps：打开 C-SON 应用程序
  • SON 用例
    • 以 RAN 为中心的用例
    • 与多域核心传输相关的用例

第4章下一代SON实现的主要趋势

  • Open RAN/vRAN（虚拟化 RAN）架构
    • 使用 RIC、xApps 和 rApps 实现 RAN 自动化和智能化
  • 小型基站、HetNet 和 RAN 的高密度
    • 即插即用小型基站
    • 为SON调整UDN（超高密度网络）
  • 共享/免许可频段
    • 使用 SON 动态管理频带
  • MEC（多路访问边缘计算）
    • 与 SON 协同的可能性
  • 网络切片
    • 5G 网络中网络切片的 SON 机制
  • 大数据和高级分析
    • 利用大数据最大限度地发挥 SON 的优势
    • 预测和行为分析的重要性
  • AI（人工智能）和 ML（机器学习）
    • 开发自学习 SON 引擎
    • 深度学习：零接触移动网络的实现
  • NFV（网络功能虚拟化）
    • 启用 SON 驱动的 VNF/CNF 部署
  • SDN（软件定义网络）和可编程性
    • 在传输网络中使用 SDN 控制器作为 SON 平台
  • 云计算
    • 提升C-SON的可扩展性和弹性
  • 其他趋势和互补技术
    • 专用 4G/5G 网络
    • FWA（固定无线接入）
    • DPI（深度数据包检测）
    • 用于自卫的数字安全
    • 用于物联网应用的 SON 功能
    • 针对工业 5G 应用的基于用户的分析和优化
    • D2D（设备到设备）通信和对新用例的支持

第 5 章标准化、监管和联合倡议

  • 3GPP（第三代合作伙伴计划）
    • SON功能的3GPP标准化
    • LTE SON 的特点
    • 5G NR SON 的特点
    • 3GPP 规范的 SON 特性的实现方法
  • O-RAN 联盟
    • Open RAN RIC 架构规范
    • xApp 和 rApp 的用例
  • OSA（开放式空中接口软件联盟）
    • M5G (MOSAIC5G) 项目：灵活的 RAN/核心控制器
  • TIP（电信基础设施项目）
    • RIA（RAN 智能与自动化）项目
  • ONF（开放网络基金会）
    • SD-RAN 项目：近实时 RIC 和 Exemplar xApps
  • Linux 基金会的 ONAP（开放网络自动化平台）
    • OOF（ONAP 优化框架）- 用于 5G 网络的 SON
    • Open RAN RIC 集成接口支持
  • SCF（小型蜂窝论坛）
    • 4G/5G 小型基站 SON 和编排
  • OSSii（运营支持系统互操作性计划）
    • 启用多供应商 SON 互操作性
  • NGMN 联盟
    • SON 计划的概念
    • 多供应商 SON 部署建议
    • 用于部署、运营和管理 5G 网络的 SON 功能
  • 其他

第 6 章 SON 部署：案例研究

  • AT&T
    • 供应商选择
    • SON 实施审查
    • 结果和未来计划
  • Bell Canada
  • Bharti Airtel
  • BT Group
  • China Mobile
  • Elisa
  • Globe Telecom
  • KDDI Corporation
  • MegaFon
  • NTT DoCoMo
  • Ooredoo
  • Orange
  • Singtel
  • SK Telecom
  • Telecom Argentina
  • Telefónica Group
  • TIM (Telecom Italia Mobile)
  • Turkcell
  • Verizon Communications
  • Vodafone Group
  • 其他最近的发展和正在进行的项目
    • beCloud(Belarusian Cloud Technologies)：支持 AI 的网络自动化和性能管理
    • Beeline Russia：利用 C-SON 技术改变移动体验
    • Betacom：通过 RAN 自动化加速企业私有 5G 的采用
    • BTC (Botswana Telecommunications Corporation)：用于国家网络优化的 SON
    • Celona：面向企业的自组织 5G LAN 解决方案
    • América Móvil：通过基于 SON 的自动化加速 5G 部署
    • DISH Network Corporation：基于 RIC 的自定义 RAN 的可编程性和智能
    • DT (Deutsche Telekom)：在柏林进行 SD-RAN 4G/5G 室外现场试验
    • KPN：SON 驱动的网络优化自动化
    • Kyivstar：利用 C-SON 提升网络性能
    • Liberty Global：建立客户至上的网络
    • LTT (Libya Telecom &Technology)：全国 RAN 自动化
    • NEC Corporation：自学本地 5G 网络
    • Opticoms：优化符合 Open RAN 标准的私有 5G 网络
    • Rakuten Mobile：用于 RAN 自动化应用的嵌入式 RIC
    • Smart Communications (PLDT)：实现多供应商 4G/5G 网络自动化
    • Smartfren：C-SON 技术促进网络緻密化和 HetNet 管理
    • STC (Saudi Telecom Company)：自动化网络运营并推动 5G 转型
    • Telkomsel：SON 的自动网络优化
    • Telstra：加速移动网络自动化
    • Zain Group：SON 带来更好的性能

第 7 章生态系统中的主要参与者

  • Aarna Networks
  • Abside Networks
  • Accedian
  • Accelleran
  • Accuver (InnoWireless)
  • Actiontec Electronics
  • AI-LINK
  • AirHop Communications
  • Airspan Networks
  • AiVader
  • Aliniant
  • Allot
  • Alpha Networks
  • Altiostar (Rakuten Symphony)
  • Amazon/AWS (Amazon Web Services)
  • Amdocs
  • Anktion (Fujian) Technology
  • Anritsu
  • Arcadyan Technology Corporation (Compal Electronics)
  • Argela
  • Aria Networks
  • ArrayComm (Chengdu ArrayComm Wireless Technologies)
  • Artemis Networks
  • Artiza Networks
  • Arukona
  • Askey Computer Corporation (ASUS - ASUSTeK Computer)
  • ASOCS
  • Aspire Technology (NEC Corporation)
  • ASTRI (Hong Kong Applied Science and Technology Research Institute)
  • ATDI
  • Atesio
  • Atrinet
  • Aurora Insight
  • Aviat Networks
  • Azcom Technology
  • Baicells
  • BandwidthX
  • BLiNQ Networks (CCI - Communication Components Inc.)
  • Blu Wireless
  • Blue Danube Systems (NEC Corporation)
  • BTI Wireless
  • B-Yond
  • CableFree (Wireless Excellence)
  • Cambium Networks
  • Capgemini Engineering
  • Casa Systems
  • CBNG (Cambridge Broadband Networks Group)
  • CCS - Cambridge Communication Systems (ADTRAN)
  • Celfinet (Cyient)
  • CellOnyx
  • Cellwize (Qualcomm)
  • CelPlan Technologies
  • CGI
  • Chengdu NTS
  • CICT - China Information and Communication Technology Group (China Xinke Group)
  • Ciena Corporation
  • CIG (Cambridge Industries Group)
  • Cisco Systems
  • Cohere Technologies
  • Comarch
  • Comba Telecom
  • CommAgility (Wireless Telecom Group)
  • CommScope
  • COMSovereign
  • Contela
  • Continual
  • Corning
  • Creanord
  • DeepSig
  • Dell Technologies
  • DGS (Digital Global Systems)
  • Digitata
  • D-Link Corporation
  • DZS
  • ECE (European Communications Engineering)
  • EDX Wireless
  • eino
  • Elisa Polystar
  • Equiendo
  • Ericsson
  • Errigal
  • ETRI (Electronics & Telecommunications Research Institute, South Korea)
  • EXFO
  • Fairspectrum
  • Federated Wireless
  • Flash Networks
  • Forsk
  • Foxconn (Hon Hai Technology Group)
  • Fraunhofer HHI (Heinrich Hertz Institute)
  • Fujitsu
  • Gemtek Technology
  • GENEViSiO (QNAP Systems)
  • GenXComm
  • Gigamon
  • GigaTera Communications (KMW)
  • Google (Alphabet)
  • Groundhog Technologies
  • Guavus (Thales)
  • HCL Technologies
  • Helios (Fujian Helios Technologies)
  • HFR Networks
  • Highstreet Technologies
  • Hitachi
  • HPE (Hewlett Packard Enterprise)
  • HSC (Hughes Systique Corporation)
  • Huawei
  • iBwave Solutions
  • iConNext
  • Infinera
  • Infosys
  • InfoVista
  • Inmanta
  • Innovile
  • InnoWireless
  • Intel Corporation
  • InterDigital
  • Intracom Telecom
  • Inventec Corporation
  • ISCO International
  • IS-Wireless
  • ITRI (Industrial Technology Research Institute, Taiwan)
  • JMA Wireless
  • JRC (Japan Radio Company)
  • Juniper Networks
  • Key Bridge Wireless
  • Keysight Technologies
  • Kleos
  • KMW
  • Kumu Networks
  • Lemko Corporation
  • Lenovo
  • Lextrum (COMSovereign)
  • Lime Microsystems
  • LIONS Technology
  • LITE-ON Technology Corporation
  • LS telcom
  • LuxCarta
  • MantisNet
  • Marvell Technology
  • Mavenir
  • Meta Connectivity
  • MicroNova
  • Microsoft Corporation
  • MikroTik
  • MitraStar Technology (Unizyx Holding Corporation)
  • MYCOM OSI (Amdocs)
  • Nash Technologies
  • NEC Corporation
  • Net AI
  • Netcracker Technology (NEC Corporation)
  • NETSCOUT Systems
  • Netsia (Argela)
  • New H3C Technologies (Tsinghua Unigroup)
  • New Postcom Equipment
  • Nextivity

Synopsis

SON (Self-Organizing Network) technology minimizes the lifecycle cost of running a mobile network by eliminating manual configuration of network elements at the time of deployment right through to dynamic optimization and troubleshooting during operation. Besides improving network performance and customer experience, SON can significantly reduce the cost of mobile operator services, improving the OpEx-to-revenue ratio and deferring avoidable CapEx.

Early adopters of SON have already witnessed a multitude of benefits in the form of accelerated 5G NR and LTE RAN (Radio Access Network) rollout times, simplified network upgrades, fewer dropped calls, improved call setup success rates, higher end user throughput, alleviation of congestion during special events, increased subscriber satisfaction and loyalty, operational efficiencies such as energy and cost savings, and freeing up radio engineers from repetitive manual tasks.

Although SON was originally developed as an operational approach to streamline and automate cellular RAN deployment and optimization, mobile operators and vendors are increasingly focusing on integrating new capabilities such as self-protection against digital security threats and self-learning through AI (Artificial Intelligence) techniques, as well as extending the scope of SON beyond the RAN to include both mobile core and transport network segments - which will be critical to address 5G requirements such as end-to-end network slicing.

In addition, with the cellular industry's ongoing shift towards open interfaces, virtualization and software-driven networking, the SON ecosystem is progressively transitioning from the traditional D-SON (Distributed SON) and C-SON (Centralized SON) approach to open standards-based components supporting RAN programmability for advanced automation and intelligent control.

The surging popularity of innovative Open RAN and vRAN (Virtualized RAN) architectures has reignited the traditionally niche and proprietary product-driven SON market with a host of open standards-compliant RIC (RAN Intelligent Controller), xApp and rApp offerings, which are capable of supporting both near real-time D-SON and non real-time C-SON capabilities for RAN automation and optimization needs.

SNS Telecom & IT estimates that global spending on RIC platforms, xApps and rApps will reach $120 Million in 2023 as initial implementations move from field trials to production-grade deployments. With commercial maturity, the submarket is further expected to quintuple to nearly $600 Million by the end of 2025. Annual investments in the wider SON market - which includes licensing of embedded D-SON features, third party C-SON functions and associated OSS platforms, in-house SON capabilities internally developed by mobile operators, and SON-related professional services across the RAN, mobile core and transport domains - are expected to grow at a CAGR of approximately 7% during the same period.

The "SON (Self-Organizing Networks) in the 5G & Open RAN Era: 2022 - 2030 - Opportunities, Challenges, Strategies & Forecasts" report presents a detailed assessment of the SON market, including the value chain, market drivers, barriers to uptake, enabling technologies, functional areas, use cases, key trends, future roadmap, standardization, case studies, ecosystem player profiles and strategies. The report also provides global and regional market size forecasts for both SON and conventional mobile network optimization from 2022 till 2030, including submarket projections for three network segments, six SON architecture categories, four access technologies and five regional submarkets.

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:

  • The surging popularity of innovative Open RAN and vRAN (Virtualized RAN) architectures has reignited the traditionally niche and proprietary product-driven SON market with a host of open standards-compliant RIC (RAN Intelligent Controller), xApp and rApp offerings, which are capable of supporting both near real-time D-SON and non real-time C-SON capabilities for RAN automation and optimization needs.
  • SNS Telecom & IT estimates that global spending on RIC platforms, xApps and rApps will reach $120 Million in 2023 as initial implementations move from field trials to production-grade deployments. With commercial maturity, the submarket is further expected to quintuple to nearly $600 Million by the end of 2025.
  • Annual investments in the wider SON market - which includes licensing of embedded D-SON features, third party C-SON functions and associated OSS platforms, in-house SON capabilities internally developed by mobile operators, and SON-related professional services across the RAN, mobile core and transport domains - are expected to grow at a CAGR of approximately 7% during the same period.
  • The third party SON vendor ecosystem is exhibiting signs of consolidation, with several prominent M&A deals such as Qualcomm's recent acquisition of C-SON specialist Cellwize - in a bid to strengthen its 5G RAN infrastructure offerings, Elisa Automate's merger with Polystar to form Elisa Polystar, and HCL's acquisition of Cisco's SON technology business.
  • However, on the other hand, newer suppliers are also beginning to emerge - extending from VMware, Juniper Networks and other RIC platform providers to x/rApp specialists such as Cohere Technologies, DeepSig, Groundhog Technologies, Subex, B-Yond, Net AI and RIMEDO Labs.
  • SON capabilities are playing a pivotal role in the ongoing proliferation of private 4G/5G networks, as evident from a growing number of cross-sector partnerships. For example, private wireless service provider Betacom is collaborating with Qualcomm to accelerate enterprise adoption of private 5G networks by combining the former's 5GaaS (5G-as-a-Service) offering with the latter's enablement ecosystem, including the Cellwize RAN automation and management platform. Similarly, Germany-based systems integrator Opticoms has entered into a partnership with SON specialist Innovile to automate and optimize Open RAN standards-compliant private 5G networks.
  • Over the last two years, with the steep rise of mobile data consumption in residential areas during the COVID-19 pandemic-imposed lockdowns, mobile operators - despite coping relatively well - have recognized the importance of a more dynamic and automated approach to the optimization of network assets in order to provide a consistent and seamless user experience.
  • The 2020-2022 period saw large-scale C-SON deployments by several operators, including but not limited to Verizon, EE (BT Group), Orange, Telefónica, Turkcell, beCloud (Belarusian Cloud Technologies), VEON, Ooredoo, Zain, BTC (Botswana Telecommunications Corporation), LTT (Libya Telecom & Technology), Telstra, Singtel, Telkomsel, Globe Telecom, Smart Communications (PLDT), and Telecom Argentina.

Topics Covered

The report covers the following topics:

  • Introduction to SON
  • Value chain and ecosystem structure
  • Market drivers and challenges
  • SON technology, architecture and functional areas
  • D-SON (Distributed SON), C-SON (Centralized SON), H-SON (Hybrid SON), RIC (RAN Intelligent Controller), xApps and rApps
  • Review of over 40 SON use cases across the RAN, core and transport domains, ranging from ANR (Automatic Neighbor Relations) and rapid equipment configuration to advanced traffic steering, QoE-based optimization and automated anomaly detection
  • Key trends in next-generation 5G SON implementations, including Open RAN and vRAN (Virtualized RAN) architectures, dynamic spectrum management, network slicing, edge computing, Big Data, advanced analytics, AI (Artificial Intelligence)/ML (Machine Learning) and zero-touch automation
  • Case studies of 20 commercial-scale SON deployments and examination of ongoing projects covering both traditional D-SON/C-SON and RIC-x/rApp approaches
  • Future roadmap for the SON market
  • Standardization, regulatory and collaborative initiatives
  • Profiles and strategies of more than 230 ecosystem players
  • Strategic recommendations for SON solution providers and mobile operators
  • Market analysis and forecasts from 2022 till 2030

Forecast Segmentation

Market forecasts are provided for each of the following submarkets and their subcategories:

SON & Mobile Network Optimization

  • SON
  • Conventional Mobile Network Planning & Optimization

SON Network Segment Submarkets

  • RAN (Radio Access Network)
  • Mobile Core
  • Transport (Fronthaul, Midhaul & Backhaul)

RAN Segment SON Architecture Submarkets

  • Traditional D-SON & C-SON
    • Embedded D-SON (Distributed SON) Features
    • Third Party C-SON (Centralized SON) & OSS Platforms
  • Open RAN RIC, xApps & rApps
    • RIC (RAN Intelligent Controller) Platforms
    • Near Real-Time xApps
    • Non Real-Time rApps
    • Mobile Operators' In-House SON Tools & Systems

SON Access Network Technology Submarkets

  • 2G & 3G
  • LTE
  • 5G
  • Wi-Fi & Others

Regional Markets

  • North America
  • Asia Pacific
  • Europe
  • Middle East & Africa
  • Latin & Central America

Key Questions Answered:

The report provides answers to the following key questions:

  • How big is the SON opportunity?
  • What trends, drivers and challenges are influencing its growth?
  • What will the market size be in 2025, and at what rate will it grow?
  • Which submarkets and regions will see the highest percentage of growth?
  • How do SON investments compare with spending on conventional mobile network optimization?
  • What are the practical, quantifiable benefits of SON - based on live, commercial deployments?
  • How can mobile operators capitalize on SON to ensure optimal network performance, improve customer experience, reduce costs, and drive revenue growth?
  • What is the status of D-SON and C-SON adoption worldwide?
  • When will open standards-based RIC platforms, xApps and rApps replace the traditional SON approach?
  • What are the prospects of AI/ML-driven automation in the SON market?
  • What opportunities exist for SON capabilities in the mobile core and transport network domains?
  • How can SON ease the deployment of private 4G/5G networks for enterprises and vertical industries?
  • In what way will SON facilitate network slicing and other advanced 5G capabilities?
  • How does SON impact mobile network optimization engineers?
  • Who are the key ecosystem players, and what are their strategies?
  • What strategies should SON solution providers and mobile operators adopt to remain competitive?

Table of Contents

Chapter 1: Introduction

  • 1.1. Executive Summary
  • 1.2. Topics Covered
  • 1.3. Forecast Segmentation
  • 1.4. Key Questions Answered
  • 1.5. Key Findings
  • 1.6. Methodology
  • 1.7. Target Audience
  • 1.8. Companies & Organizations Mentioned

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 & End User Data
    • 2.1.3. Post-Processing, Optimization & Policy Enforcement
  • 2.2. The SON (Self-Organizing Network) 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
    • 2.3.4. Self-Protection
    • 2.3.5. Self-Learning
  • 2.4. SON Value Chain
    • 2.4.1. SON, xApp/rApp & Automation Specialists
    • 2.4.2. OSS & RIC Platform Providers
    • 2.4.3. RAN, Core & Transport Network Equipment Suppliers
    • 2.4.4. Wireless Service Providers
      • 2.4.4.1. National Mobile Operators
      • 2.4.4.2. Fixed-Line Service Providers
      • 2.4.4.3. Private 4G/5G Network Operators
      • 2.4.4.4. Neutral Hosts
    • 2.4.5. End Users
      • 2.4.5.1. Consumers
      • 2.4.5.2. Enterprises & Vertical Industries
    • 2.4.6. Other Ecosystem Players
  • 2.5. Market Drivers
    • 2.5.1. The 5G & Open RAN Era: Continued Infrastructure Investments
    • 2.5.2. Optimization in Complex Multi-RAN Environments
    • 2.5.3. OpEx & CapEx Reduction: The Cost Savings Potential
    • 2.5.4. Improving Subscriber Experience & Churn Reduction
    • 2.5.5. Power Savings: Towards Greener Mobile Networks
    • 2.5.6. Alleviating Congestion With Traffic Management
    • 2.5.7. Enabling Plug & Play Deployment of Small Cells
    • 2.5.8. Growing Adoption of Private 4G/5G Networks
  • 2.6. Market Barriers
    • 2.6.1. Complexity of Implementation
    • 2.6.2. Reorganization & Changes to Standard Engineering Procedures
    • 2.6.3. Lack of Trust in Automation
    • 2.6.4. Proprietary SON Algorithms
    • 2.6.5. Coordination Between Distributed & Centralized SON
    • 2.6.6. Network Security Concerns: New Interfaces & Lack of Monitoring

Chapter 3: SON Technology, Implementation Architectures & Use Cases

  • 3.1. Where Does SON Sit Within a Mobile Network?
    • 3.1.1. RAN
    • 3.1.2. Mobile Core
    • 3.1.3. Transport (Fronthaul, Midhaul & Backhaul)
    • 3.1.4. Device-Assisted SON
  • 3.2. Traditional SON Architecture
    • 3.2.1. D-SON (Distributed SON)
    • 3.2.2. C-SON (Centralized SON)
    • 3.2.3. H-SON (Hybrid SON)
  • 3.3. Open Standards-Compliant RIC, xApps & rApps
    • 3.3.1. RIC (RAN Intelligent Controller)
      • 3.3.1.1. Near-RT (Real-Time) RIC
      • 3.3.1.2. Non-RT (Real-Time) RIC
    • 3.3.2. xApps: Open D-SON Applications
    • 3.3.3. rApps: Open C-SON Applications
  • 3.4. SON Use Cases
    • 3.4.1. RAN-Centric Use Cases
      • 3.4.1.1. ANR (Automatic Neighbor Relations)
      • 3.4.1.2. CNR (Centralized Neighbor Relations)
      • 3.4.1.3. PCI (Physical Cell ID) Allocation & Conflict Resolution
      • 3.4.1.4. CCO (Coverage & Capacity Optimization)
      • 3.4.1.5. MRO (Mobility Robustness Optimization)
      • 3.4.1.6. MLB (Mobility Load Balancing)
      • 3.4.1.7. RACH (Random Access Channel) Optimization
      • 3.4.1.8. ICIC (Inter-Cell Interference Coordination) & eICIC (Enhanced ICIC)
      • 3.4.1.9. COD/COC (Cell Outage Detection & Compensation)
      • 3.4.1.10. MDT (Minimization of Drive Tests)
      • 3.4.1.11. Advanced Traffic Steering
      • 3.4.1.12. Automated Anomaly Detection
      • 3.4.1.13. Massive MIMO & Beamforming Optimization
      • 3.4.1.14. 4G-5G Dual Connectivity Management
      • 3.4.1.15. RAN Slice Management
      • 3.4.1.16. DSS (Dynamic Spectrum Sharing)
      • 3.4.1.17. Frequency Layer Management
      • 3.4.1.18. BBU (Baseband Unit) Resource Pooling
      • 3.4.1.19. Radio Resource Allocation for Complex Vertical Applications
      • 3.4.1.20. Handover Management in V2X Communications Scenarios
      • 3.4.1.21. Rapid Plug & Play Configuration of Small Cells
      • 3.4.1.22. DAS (Distributed Antenna System) Optimization
    • 3.4.2. Multi-Domain, Core & Transport-Related Use Cases
      • 3.4.2.1. Self-Configuration & Testing of Network Elements
      • 3.4.2.2. Domain Connectivity Management
      • 3.4.2.3. Automated Inventory Checks
      • 3.4.2.4. AIC (Automated Inconsistency Correction)
      • 3.4.2.5. Self-Healing of Network Faults
      • 3.4.2.6. Signaling Storm Protection
      • 3.4.2.7. Energy Efficiency & Savings
      • 3.4.2.8. QoS & QoE-Based Optimization
      • 3.4.2.9. Congestion Prediction & Management
      • 3.4.2.10. AI-Enabled Performance Diagnostics
      • 3.4.2.11. Industrial IoT Optimization
      • 3.4.2.12. Core Network Automation
      • 3.4.2.13. Network Slicing Resource Allocation
      • 3.4.2.14. Optimization of VNFs & CNFs
      • 3.4.2.15. Auto-Provisioning of Transport Links
      • 3.4.2.16. Transport Network Bandwidth Optimization
      • 3.4.2.17. Wireless Transport Interference Management
      • 3.4.2.18. Seamless Vendor Infrastructure Swap
      • 3.4.2.19. SON Coordination Management
      • 3.4.2.20. Cognitive & Self-Learning Networks

Chapter 4: Key Trends in Next-Generation SON Implementations

  • 4.1. Open RAN & vRAN (Virtualized RAN) Architectures
    • 4.1.1. Enabling RAN Automation & Intelligence With RIC, xApps & rApps
  • 4.2. Small Cells, HetNets & RAN Densification
    • 4.2.1. Plug & Play Small Cells
    • 4.2.2. SON-Enabled Coordination of UDNs (Ultra-Dense Networks)
  • 4.3. Shared & Unlicensed Spectrum
    • 4.3.1. Dynamic Management of Spectrum Using SON
  • 4.4. MEC (Multi-Access Edge Computing)
    • 4.4.1. Potential Synergies With SON
  • 4.5. Network Slicing
    • 4.5.1. SON Mechanisms for Network Slicing in 5G Networks
  • 4.6. Big Data & Advanced Analytics
    • 4.6.1. Maximizing the Benefits of SON With Big Data
    • 4.6.2. The Importance of Predictive & Behavioral Analytics
  • 4.7. AI (Artificial Intelligence) & ML (Machine Learning)
    • 4.7.1. Towards Self-Learning SON Engines
    • 4.7.2. Deep Learning: Enabling Zero-Touch Mobile Networks
  • 4.8. NFV (Network Functions Virtualization)
    • 4.8.1. Enabling SON-Driven Deployment of VNFs & CNFs
  • 4.9. SDN (Software-Defined Networking) & Programmability
    • 4.9.1. Using the SDN Controller as a Platform for SON in Transport Networks
  • 4.10. Cloud Computing
    • 4.10.1. Facilitating C-SON Scalability & Elasticity
  • 4.11. Other Trends & Complementary Technologies
    • 4.11.1. Private 4G/5G Networks
    • 4.11.2. FWA (Fixed Wireless Access)
    • 4.11.3. DPI (Deep Packet Inspection)
    • 4.11.4. Digital Security for Self-Protection
    • 4.11.5. SON Capabilities for IoT Applications
    • 4.11.6. User-Based Profiling & Optimization for Vertical 5G Applications
    • 4.11.7. Addressing D2D (Device-to-Device) Communications & New Use Cases

Chapter 5: Standardization, Regulatory & Collaborative Initiatives

  • 5.1. 3GPP (Third Generation Partnership Project)
    • 5.1.1. 3GPP Standardization of SON Capabilities
    • 5.1.2. LTE SON Features
      • 5.1.2.1. Release 8
      • 5.1.2.2. Release 9
      • 5.1.2.3. Release 10
      • 5.1.2.4. Release 11
      • 5.1.2.5. Release 12
      • 5.1.2.6. Releases 13 & 14
    • 5.1.3. 5G NR SON Features
      • 5.1.3.1. Release 15
      • 5.1.3.2. Release 16
      • 5.1.3.3. Release 17
      • 5.1.3.4. Release 18 & Beyond
    • 5.1.4. Implementation Approach for 3GPP-Specified SON Features
  • 5.2. O-RAN Alliance
    • 5.2.1. Open RAN RIC Architecture Specifications
    • 5.2.2. xApp & rApp Use Cases
  • 5.3. OSA (OpenAirInterface Software Alliance)
    • 5.3.1. M5G (MOSAIC5G) Project: Flexible RAN & Core Controllers
  • 5.4. TIP (Telecom Infra Project)
    • 5.4.1. RIA (RAN Intelligence & Automation) Project
  • 5.5. ONF (Open Networking Foundation)
    • 5.5.1. SD-RAN Project: Near Real-Time RIC & Exemplar xApps
  • 5.6. Linux Foundation's ONAP (Open Network Automation Platform)
    • 5.6.1. OOF (ONAP Optimization Framework)-SON for 5G Networks
    • 5.6.2. Interface Support for Open RAN RIC Integration
  • 5.7. SCF (Small Cell Forum)
    • 5.7.1. 4G/5G Small Cell SON & Orchestration
  • 5.8. OSSii (Operations Support Systems Interoperability Initiative)
    • 5.8.1. Enabling Multi-Vendor SON Interoperability
  • 5.9. NGMN Alliance
    • 5.9.1. Conception of the SON Initiative
    • 5.9.2. Recommendations for Multi-Vendor SON Deployment
    • 5.9.3. SON Capabilities for 5G Network Deployment, Operation & Management
  • 5.10. Others

Chapter 6: SON Deployment Case Studies

  • 6.1. AT&T
    • 6.1.1. Vendor Selection
    • 6.1.2. SON Deployment Review
    • 6.1.3. Results & Future Plans
  • 6.2. Bell Canada
    • 6.2.1. Vendor Selection
    • 6.2.2. SON Deployment Review
    • 6.2.3. Results & Future Plans
  • 6.3. Bharti Airtel
    • 6.3.1. Vendor Selection
    • 6.3.2. SON Deployment Review
    • 6.3.3. Results & Future Plans
  • 6.4. BT Group
    • 6.4.1. Vendor Selection
    • 6.4.2. SON Deployment Review
    • 6.4.3. Results & Future Plans
  • 6.5. China Mobile
    • 6.5.1. Vendor Selection
    • 6.5.2. SON Deployment Review
    • 6.5.3. Results & Future Plans
  • 6.6. Elisa
    • 6.6.1. Vendor Selection
    • 6.6.2. SON Deployment Review
    • 6.6.3. Results & Future Plans
  • 6.7. Globe Telecom
    • 6.7.1. Vendor Selection
    • 6.7.2. SON Deployment Review
    • 6.7.3. Results & Future Plans
  • 6.8. KDDI Corporation
    • 6.8.1. Vendor Selection
    • 6.8.2. SON Deployment Review
    • 6.8.3. Results & Future Plans
  • 6.9. MegaFon
    • 6.9.1. Vendor Selection
    • 6.9.2. SON Deployment Review
    • 6.9.3. Results & Future Plans
  • 6.10. NTT DoCoMo
    • 6.10.1. Vendor Selection
    • 6.10.2. SON Deployment Review
    • 6.10.3. Results & Future Plans
  • 6.11. Ooredoo
    • 6.11.1. Vendor Selection
    • 6.11.2. SON Deployment Review
    • 6.11.3. Results & Future Plans
  • 6.12. Orange
    • 6.12.1. Vendor Selection
    • 6.12.2. SON Deployment Review
    • 6.12.3. Results & Future Plans
  • 6.13. Singtel
    • 6.13.1. Vendor Selection
    • 6.13.2. SON Deployment Review
    • 6.13.3. Results & Future Plans
  • 6.14. SK Telecom
    • 6.14.1. Vendor Selection
    • 6.14.2. SON Deployment Review
    • 6.14.3. Results & Future Plans
  • 6.15. Telecom Argentina
    • 6.15.1. Vendor Selection
    • 6.15.2. SON Deployment Review
    • 6.15.3. Results & Future Plans
  • 6.16. Telefónica Group
    • 6.16.1. Vendor Selection
    • 6.16.2. SON Deployment Review
    • 6.16.3. Results & Future Plans
  • 6.17. TIM (Telecom Italia Mobile)
    • 6.17.1. Vendor Selection
    • 6.17.2. SON Deployment Review
    • 6.17.3. Results & Future Plans
  • 6.18. Turkcell
    • 6.18.1. Vendor Selection
    • 6.18.2. SON Deployment Review
    • 6.18.3. Results & Future Plans
  • 6.19. Verizon Communications
    • 6.19.1. Vendor Selection
    • 6.19.2. SON Deployment Review
    • 6.19.3. Results & Future Plans
  • 6.20. Vodafone Group
    • 6.20.1. Vendor Selection
    • 6.20.2. SON Deployment Review
    • 6.20.3. Results & Future Plans
  • 6.21. Other Recent Deployments & Ongoing Projects
    • 6.21.1. beCloud (Belarusian Cloud Technologies): AI-Enabled Network Automation & Performance Management
    • 6.21.2. Beeline Russia: Transforming the Mobile Experience Using C-SON Technology
    • 6.21.3. Betacom: Accelerating Enterprise Private 5G Adoption With RAN Automation
    • 6.21.4. BTC (Botswana Telecommunications Corporation): SON for Nationwide Network Optimization
    • 6.21.5. Celona: Self-Organizing 5G LAN Solution for Enterprises
    • 6.21.6. América Móvil: Accelerating 5G Rollouts Through SON-Based Automation
    • 6.21.7. DISH Network Corporation: RIC-Based Custom RAN Programmability & Intelligence
    • 6.21.8. DT (Deutsche Telekom): Berlin SD-RAN 4G/5G Outdoor Field Trial
    • 6.21.9. KPN: SON-Driven Automation for Network Optimization
    • 6.21.10. Kyivstar: Leveraging C-SON to Enhance Network Performance
    • 6.21.11. Liberty Global: Building a Customer-First Network
    • 6.21.12. LTT (Libya Telecom & Technology): Nationwide RAN Automation
    • 6.21.13. NEC Corporation: Self-Learning Local 5G Networks
    • 6.21.14. Opticoms: Optimizing Open RAN-Compliant Private 5G Networks
    • 6.21.15. Rakuten Mobile: Embedded RIC for RAN Automation Applications
    • 6.21.16. Smart Communications (PLDT): Enabling Multi-Vendor 4G/5G Network Automation
    • 6.21.17. Smartfren: Facilitating Network Densification & HetNet Management With C-SON Technology
    • 6.21.18. STC (Saudi Telecom Company): Automating Network Operations & Driving 5G Transformation
    • 6.21.19. Telkomsel: SON-Enabled Automated Network Optimization
    • 6.21.20. Telstra: Boosting Mobile Network Automation
    • 6.21.21. Zain Group: SON for Performance Enhancement

Chapter 7: Key Ecosystem Players

  • 7.1. Aarna Networks
  • 7.2. Abside Networks
  • 7.3. Accedian
  • 7.4. Accelleran
  • 7.5. Accuver (InnoWireless)
  • 7.6. Actiontec Electronics
  • 7.7. AI-LINK
  • 7.8. AirHop Communications
  • 7.9. Airspan Networks
  • 7.10. AiVader
  • 7.11. Aliniant
  • 7.12. Allot
  • 7.13. Alpha Networks
  • 7.14. Altiostar (Rakuten Symphony)
  • 7.15. Amazon/AWS (Amazon Web Services)
  • 7.16. Amdocs
  • 7.17. Anktion (Fujian) Technology
  • 7.18. Anritsu
  • 7.19. Arcadyan Technology Corporation (Compal Electronics)
  • 7.20. Argela
  • 7.21. Aria Networks
  • 7.22. ArrayComm (Chengdu ArrayComm Wireless Technologies)
  • 7.23. Artemis Networks
  • 7.24. Artiza Networks
  • 7.25. Arukona
  • 7.26. Askey Computer Corporation (ASUS - ASUSTeK Computer)
  • 7.27. ASOCS
  • 7.28. Aspire Technology (NEC Corporation)
  • 7.29. ASTRI (Hong Kong Applied Science and Technology Research Institute)
  • 7.30. ATDI
  • 7.31. Atesio
  • 7.32. Atrinet
  • 7.33. Aurora Insight
  • 7.34. Aviat Networks
  • 7.35. Azcom Technology
  • 7.36. Baicells
  • 7.37. BandwidthX
  • 7.38. BLiNQ Networks (CCI - Communication Components Inc.)
  • 7.39. Blu Wireless
  • 7.40. Blue Danube Systems (NEC Corporation)
  • 7.41. BTI Wireless
  • 7.42. B-Yond
  • 7.43. CableFree (Wireless Excellence)
  • 7.44. Cambium Networks
  • 7.45. Capgemini Engineering
  • 7.46. Casa Systems
  • 7.47. CBNG (Cambridge Broadband Networks Group)
  • 7.48. CCS - Cambridge Communication Systems (ADTRAN)
  • 7.49. Celfinet (Cyient)
  • 7.50. CellOnyx
  • 7.51. Cellwize (Qualcomm)
  • 7.52. CelPlan Technologies
  • 7.53. CGI
  • 7.54. Chengdu NTS
  • 7.55. CICT - China Information and Communication Technology Group (China Xinke Group)
  • 7.56. Ciena Corporation
  • 7.57. CIG (Cambridge Industries Group)
  • 7.58. Cisco Systems
  • 7.59. Cohere Technologies
  • 7.60. Comarch
  • 7.61. Comba Telecom
  • 7.62. CommAgility (Wireless Telecom Group)
  • 7.63. CommScope
  • 7.64. COMSovereign
  • 7.65. Contela
  • 7.66. Continual
  • 7.67. Corning
  • 7.68. Creanord
  • 7.69. DeepSig
  • 7.70. Dell Technologies
  • 7.71. DGS (Digital Global Systems)
  • 7.72. Digitata
  • 7.73. D-Link Corporation
  • 7.74. DZS
  • 7.75. ECE (European Communications Engineering)
  • 7.76. EDX Wireless
  • 7.77. eino
  • 7.78. Elisa Polystar
  • 7.79. Equiendo
  • 7.80. Ericsson
  • 7.81. Errigal
  • 7.82. ETRI (Electronics & Telecommunications Research Institute, South Korea)
  • 7.83. EXFO
  • 7.84. Fairspectrum
  • 7.85. Federated Wireless
  • 7.86. Flash Networks
  • 7.87. Forsk
  • 7.88. Foxconn (Hon Hai Technology Group)
  • 7.89. Fraunhofer HHI (Heinrich Hertz Institute)
  • 7.90. Fujitsu
  • 7.91. Gemtek Technology
  • 7.92. GENEViSiO (QNAP Systems)
  • 7.93. GenXComm
  • 7.94. Gigamon
  • 7.95. GigaTera Communications (KMW)
  • 7.96. Google (Alphabet)
  • 7.97. Groundhog Technologies
  • 7.98. Guavus (Thales)
  • 7.99. HCL Technologies
  • 7.100. Helios (Fujian Helios Technologies)
  • 7.101. HFR Networks
  • 7.102. Highstreet Technologies
  • 7.103. Hitachi
  • 7.104. HPE (Hewlett Packard Enterprise)
  • 7.105. HSC (Hughes Systique Corporation)
  • 7.106. Huawei
  • 7.107. iBwave Solutions
  • 7.108. iConNext
  • 7.109. Infinera
  • 7.110. Infosys
  • 7.111. InfoVista
  • 7.112. Inmanta
  • 7.113. Innovile
  • 7.114. InnoWireless
  • 7.115. Intel Corporation
  • 7.116. InterDigital
  • 7.117. Intracom Telecom
  • 7.118. Inventec Corporation
  • 7.119. ISCO International
  • 7.120. IS-Wireless
  • 7.121. ITRI (Industrial Technology Research Institute, Taiwan)
  • 7.122. JMA Wireless
  • 7.123. JRC (Japan Radio Company)
  • 7.124. Juniper Networks
  • 7.125. Key Bridge Wireless
  • 7.126. Keysight Technologies
  • 7.127. Kleos
  • 7.128. KMW
  • 7.129. Kumu Networks
  • 7.130. Lemko Corporation
  • 7.131. Lenovo
  • 7.132. Lextrum (COMSovereign)
  • 7.133. Lime Microsystems
  • 7.134. LIONS Technology
  • 7.135. LITE-ON Technology Corporation
  • 7.136. LS telcom
  • 7.137. LuxCarta
  • 7.138. MantisNet
  • 7.139. Marvell Technology
  • 7.140. Mavenir
  • 7.141. Meta Connectivity
  • 7.142. MicroNova
  • 7.143. Microsoft Corporation
  • 7.144. MikroTik
  • 7.145. MitraStar Technology (Unizyx Holding Corporation)
  • 7.146. MYCOM OSI (Amdocs)
  • 7.147. Nash Technologies
  • 7.148. NEC Corporation
  • 7.149. Net AI
  • 7.150. Netcracker Technology (NEC Corporation)
  • 7.151. NETSCOUT Systems
  • 7.152. Netsia (Argela)
  • 7.153. New H3C Technologies (Tsinghua Unigroup)
  • 7.154. New Postcom Equipment
  • 7.155. Nextivity
  • 7.156. Node-H
  • 7.157. Nokia
  • 7.158. NuRAN Wireless
  • 7.159. NXP Semiconductors
  • 7.160. Oceus Networks
  • 7.161. Omnitele
  • 7.162. Opanga Networks
  • 7.163. Openet (Amdocs)
  • 7.164. P.I. Works
  • 7.165. Parallel Wireless
  • 7.166. Phluido
  • 7.167. Picocom
  • 7.168. Pivotal Commware
  • 7.169. Polte
  • 7.170. Potevio (CETC - China Electronics Technology Group Corporation)
  • 7.171. Qualcomm
  • 7.172. Quanta Computer
  • 7.173. Qucell Networks (InnoWireless)
  • 7.174. RADCOM
  • 7.175. Radisys (Reliance Industries)
  • 7.176. Rakuten Symphony
  • 7.177. Ranplan Wireless
  • 7.178. Red Hat (IBM)
  • 7.179. RED Technologies
  • 7.180. RIMEDO Labs
  • 7.181. Rivada Networks
  • 7.182. Rohde & Schwarz
  • 7.183. Ruijie Networks
  • 7.184. RunEL
  • 7.185. SageRAN (Guangzhou SageRAN Technology)
  • 7.186. Saguna Networks (COMSovereign)
  • 7.187. Samji Electronics
  • 7.188. Samsung
  • 7.189. Sandvine
  • 7.190. Sercomm Corporation
  • 7.191. Signalwing
  • 7.192. Siklu
  • 7.193. SIRADEL
  • 7.194. Skyvera (TelcoDR)
  • 7.195. SOLiD
  • 7.196. Sooktha
  • 7.197. Spectrum Effect
  • 7.198. SSC (Shared Spectrum Company)
  • 7.199. Star Solutions
  • 7.200. STL (Sterlite Technologies Ltd.)
  • 7.201. Subex
  • 7.202. Sunwave Communications
  • 7.203. Systemics-PAB
  • 7.204. T&W (Shenzhen Gongjin Electronics)
  • 7.205. Tarana Wireless
  • 7.206. TCS (Tata Consultancy Services)
  • 7.207. Tech Mahindra
  • 7.208. Tecore Networks
  • 7.209. Telrad Networks
  • 7.210. TEOCO
  • 7.211. ThinkRF
  • 7.212. TI (Texas Instruments)
  • 7.213. TietoEVRY
  • 7.214. Trópico (CPQD - Center for Research and Development in Telecommunications, Brazil)
  • 7.215. TTG International
  • 7.216. Tupl
  • 7.217. ULAK Communication
  • 7.218. Vavitel (Shenzhen Vavitel Technology)
  • 7.219. VHT (Viettel High Tech)
  • 7.220. VIAVI Solutions
  • 7.221. VMware
  • 7.222. VNC - Virtual NetCom (COMSovereign)
  • 7.223. VNL - Vihaan Networks Limited (Shyam Group)
  • 7.224. WDNA (Wireless DNA)
  • 7.225. WebRadar
  • 7.226. Wind River Systems
  • 7.227. Wipro
  • 7.228. Wiwynn (Wistron Corporation)
  • 7.229. WNC (Wistron NeWeb Corporation)
  • 7.230. XCOM Labs
  • 7.231. Xingtera
  • 7.232. ZaiNar
  • 7.233. Z-Com
  • 7.234. Zeetta Networks
  • 7.235. ZTE
  • 7.236. Zyxel (Unizyx Holding Corporation)

Chapter 8: Market Sizing & Forecasts

  • 8.1. SON & Mobile Network Optimization Revenue
  • 8.2. SON Revenue
  • 8.3. SON Revenue by Network Segment
    • 8.3.1. RAN
    • 8.3.2. Mobile Core
    • 8.3.3. Transport (Fronthaul, Midhaul & Backhaul)
  • 8.4. RAN Segment SON Revenue by Architecture: Traditional SON vs. Open RAN RIC, xApps & rApps
    • 8.4.1. Traditional D-SON & C-SON
      • 8.4.1.1. Embedded D-SON Features
      • 8.4.1.2. Third Party C-SON & OSS Platforms
    • 8.4.2. Open RAN RIC, xApps & rApps
      • 8.4.2.1. RIC Platforms
      • 8.4.2.2. Near Real-Time xApps
      • 8.4.2.3. Non Real-Time rApps
    • 8.4.3. Mobile Operators' In-House SON Tools & Systems
  • 8.5. SON Revenue by Access Network Technology
    • 8.5.1. 2G & 3G
    • 8.5.2. LTE
    • 8.5.3. 5G NR
    • 8.5.4. Wi-Fi & Others
  • 8.6. SON Revenue by Region
  • 8.7. Conventional Mobile Network Planning & Optimization Revenue
  • 8.8. Conventional Mobile Network Planning & Optimization Revenue by Region
  • 8.9. North America
    • 8.9.1. SON
    • 8.9.2. Conventional Mobile Network Planning & Optimization
  • 8.10. Asia Pacific
    • 8.10.1. SON
    • 8.10.2. Conventional Mobile Network Planning & Optimization
  • 8.11. Europe
    • 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. Latin & Central America
    • 8.13.1. SON
    • 8.13.2. Conventional Mobile Network Planning & Optimization

Chapter 9: Conclusion & Strategic Recommendations

  • 9.1. Why is the Market Poised to Grow?
  • 9.2. Future Roadmap: 2022 - 2030
    • 9.2.1. 2022 - 2025: Transition From Traditional SON to RIC Platforms, xApps & rApps
    • 9.2.2. 2026 - 2029: Commercial Maturity of Advanced AI/ML-Based SON Implementations
    • 9.2.3. 2030 & Beyond: Towards Zero-Touch 5G & 6G Network Automation
  • 9.3. Competitive Industry Landscape: Acquisitions, Alliances & Consolidation
  • 9.4. The C-SON Versus D-SON Debate
  • 9.5. Evaluating the Practical Benefits of SON
  • 9.6. Prospects of Open RAN Standards-Compliant RIC Platforms, xApps & rApps
  • 9.7. End-to-End SON: From the RAN to the Core & Transport Domains
  • 9.8. Growing Adoption of SON Capabilities for Wi-Fi & Non-3GPP Access Technologies
  • 9.9. The Importance of AI & ML-Driven SON Algorithms
  • 9.10. Improving End User Experience With QoE-Based Optimization
  • 9.11. Enabling Network Slicing & Advanced 5G Capabilities
  • 9.12. Greater Focus on Self-Protection
  • 9.13. Addressing IoT Optimization
  • 9.14. Managing Shared & Unlicensed Spectrum
  • 9.15. Easing the Deployment of Private 4G/5G Networks
  • 9.16. Assessing the Impact of SON on Optimization & Field Engineers
  • 9.17. Strategic Recommendations
    • 9.17.1. SON Solution Providers
    • 9.17.2. Mobile Operators

List of Figures

  • Figure 1: Functional Areas of SON Within the Mobile Network Lifecycle
  • Figure 2: SON Value Chain
  • Figure 3: SON Associated OpEx & CapEx Savings by Network Segment (%)
  • Figure 4: Potential Areas of SON Implementation
  • Figure 5: Mobile Fronthaul, Midhaul & Backhaul Technologies
  • Figure 6: D-SON (Distributed SON) in a Mobile Network
  • Figure 7: C-SON (Centralized SON) in a Mobile Network
  • Figure 8: H-SON (Hybrid SON) in a Mobile Network
  • Figure 9: RIC (RAN Intelligent Controller) Functional Architecture
  • Figure 10: Transition to UDNs (Ultra-Dense Networks)
  • Figure 11: Conceptual Architecture for End-to-End Network Slicing in Mobile Networks
  • Figure 12: NFV (Network Functions Virtualization) Concept
  • Figure 13: Comparison Between DPI (Deep Packet Inspection) & Shallow Packet Inspection
  • Figure 14: O-RAN Architecture
  • Figure 15: OSA's M5G (MOSAIC5G) Stack
  • Figure 16: ONF's SD-RAN Project
  • Figure 17: NGNM SON Use Cases
  • Figure 18: AT&T's SON Implementation
  • Figure 19: Elisa's In-House SON Solution
  • Figure 20: KDDI's AI-Assisted Automated Network Operation System
  • Figure 21: NTT DoCoMo's Intelligent RAN Roadmap
  • Figure 22: Orange's Vision for Cognitive PBSM (Policy-Based SON Management)
  • Figure 23: SK Telecom's Fast Data Platform for QoE-Based Automatic Network Optimization
  • Figure 24: Telefónica's SON Deployment Roadmap From 4G To 5G Rollouts
  • Figure 25: TIM's Open SON Architecture
  • Figure 26: Global SON & Mobile Network Optimization Revenue: 2022 - 2030 ($ Million)
  • Figure 27: Global SON Revenue: 2022 - 2030 ($ Million)
  • Figure 28: Global SON Revenue by Network Segment: 2022 - 2030 ($ Million)
  • Figure 29: Global SON Revenue in the RAN Segment: 2022 - 2030 ($ Million)
  • Figure 30: Global SON Revenue in the Mobile Core Segment: 2022 - 2030 ($ Million)
  • Figure 31: Global SON Revenue in the Transport (Fronthaul, Midhaul & Backhaul) Segment: 2022 - 2030 ($ Million)
  • Figure 32: Global RAN Segment SON Revenue by Architecture: 2022 - 2030 ($ Million)
  • Figure 33: Global RAN Segment Traditional D-SON & C-SON Revenue: 2022 - 2030 ($ Million)
  • Figure 34: Global RAN Segment Embedded D-SON Revenue: 2022 - 2030 ($ Million)
  • Figure 35: Global RAN Segment Third Party C-SON & OSS Platforms Revenue: 2022 - 2030 ($ Million)
  • Figure 36: Global Open RAN RIC, xApps & rApps Revenue: 2022 - 2030 ($ Million)
  • Figure 37: Global RIC Platforms Revenue: 2022 - 2030 ($ Million)
  • Figure 38: Global Near Real-Time xApps Revenue: 2022 - 2030 ($ Million)
  • Figure 39: Global Non Real-Time rApps Revenue: 2022 - 2030 ($ Million)
  • Figure 40: Global Mobile Operators' In-House SON Tools & Systems Revenue: 2022 - 2030 ($ Million)
  • Figure 41: Global SON Revenue by Access Network Technology: 2022 - 2030 ($ Million)
  • Figure 42: Global 2G & 3G SON Revenue: 2022 - 2030 ($ Million)
  • Figure 43: Global LTE SON Revenue: 2022 - 2030 ($ Million)
  • Figure 44: Global 5G NR SON Revenue: 2020 - 2030 ($ Million)
  • Figure 45: Global Wi-Fi & Other Access Technology SON Revenue: 2022 - 2030 ($ Million)
  • Figure 46: SON Revenue by Region: 2022 - 2030 ($ Million)
  • Figure 47: Global Conventional Mobile Network Planning & Optimization Revenue: 2022 - 2030 ($ Million)
  • Figure 48: Conventional Mobile Network Planning & Optimization Revenue by Region: 2022 - 2030 ($ Million)
  • Figure 49: North America SON Revenue: 2022 - 2030 ($ Million)
  • Figure 50: North America Conventional Mobile Network Planning & Optimization Revenue: 2022 - 2030 ($ Million)
  • Figure 51: Asia Pacific SON Revenue: 2022 - 2030 ($ Million)
  • Figure 52: Asia Pacific Conventional Mobile Network Planning & Optimization Revenue: 2022 - 2030 ($ Million)
  • Figure 53: Europe SON Revenue: 2022 - 2030 ($ Million)
  • Figure 54: Europe Conventional Mobile Network Planning & Optimization Revenue: 2022 - 2030 ($ Million)
  • Figure 55: Middle East & Africa SON Revenue: 2022 - 2030 ($ Million)
  • Figure 56: Middle East & Africa Conventional Mobile Network Planning & Optimization Revenue: 2022 - 2030 ($ Million)
  • Figure 57: Latin & Central America SON Revenue: 2022 - 2030 ($ Million)
  • Figure 58: Latin & Central America Conventional Mobile Network Planning & Optimization Revenue: 2022 - 2030 ($ Million)
  • Figure 59: SON Future Roadmap: 2022 - 2030
  • Figure 60: Global Spending on RIC Platforms, xApps & rApps: 2023 - 2025 ($ Million)

List of Companies Mentioned:

  • 3GPP (Third Generation Partnership Project)
  • Aarna Networks
  • Abside Networks
  • Accedian
  • Accelleran
  • Accuver
  • Actiontec Electronics
  • ADTRAN
  • AI-LINK
  • AirHop Communications
  • Airspan Networks
  • AiVader
  • Aliniant
  • Allot
  • Alpha Networks
  • Alphabet
  • Altiostar
  • Amazon
  • Amdocs
  • América Móvil
  • Anktion (Fujian) Technology
  • Anritsu
  • Arcadyan Technology Corporation
  • Argela
  • Aria Networks
  • ARIB (Association of Radio Industries and Businesses, Japan)
  • ArrayComm (Chengdu ArrayComm Wireless Technologies)
  • Artemis Networks
  • Artiza Networks
  • Arukona
  • Askey Computer Corporation
  • ASOCS
  • Aspire Technology
  • ASTRI (Hong Kong Applied Science and Technology Research Institute)
  • ASUS (ASUSTeK Computer)
  • AT&T
  • ATDI
  • Atesio
  • ATIS (Alliance for Telecommunications Industry Solutions)
  • Atrinet
  • Aurora Insight
  • Aviat Networks
  • AWS (Amazon Web Services)
  • Azcom Technology
  • Baicells
  • BandwidthX
  • beCloud (Belarusian Cloud Technologies)
  • Beeline Russia
  • Bell Canada
  • Betacom
  • Bharti Airtel
  • BLiNQ Networks
  • Blu Wireless
  • Blue Danube Systems
  • BT Group
  • BTC (Botswana Telecommunications Corporation)
  • BTI Wireless
  • B-Yond
  • CableFree (Wireless Excellence)
  • CableLabs
  • Cambium Networks
  • Capgemini Engineering
  • Casa Systems
  • CBNG (Cambridge Broadband Networks Group)
  • CCI (Communication Components Inc.)
  • CCS (Cambridge Communication Systems)
  • CCSA (China Communications Standards Association)
  • Celfinet (Cyient)
  • CellOnyx
  • Cellwize
  • Celona
  • CelPlan Technologies
  • CETC (China Electronics Technology Group Corporation)
  • CGI
  • Chengdu NTS
  • China Mobile
  • CICT - China Information and Communication Technology Group (China Xinke Group)
  • Ciena Corporation
  • CIG (Cambridge Industries Group)
  • Cisco Systems
  • Claro Colombia
  • Cohere Technologies
  • Comarch
  • Comba Telecom
  • CommAgility
  • CommScope
  • Compal Electronics
  • COMSovereign
  • Contela
  • Continual
  • Corning
  • CPQD (Center for Research and Development in Telecommunications, Brazil)
  • Creanord
  • Datang Telecom Technology & Industry Group
  • DeepSig
  • Dell Technologies
  • DGS (Digital Global Systems)
  • Digitata
  • DISH Network Corporation
  • D-Link Corporation
  • DSA (Dynamic Spectrum Alliance)
  • DT (Deutsche Telekom)
  • DZS
  • ECE (European Communications Engineering)
  • EDX Wireless
  • EE
  • eino
  • Elisa
  • Elisa Polystar
  • Equiendo
  • Ericsson
  • Errigal
  • ETRI (Electronics & Telecommunications Research Institute, South Korea)
  • ETSI (European Telecommunications Standards Institute)
  • EXFO
  • Fairspectrum
  • Federated Wireless
  • FiberHome Technologies
  • Flash Networks
  • Forsk
  • Foxconn (Hon Hai Technology Group)
  • Fraunhofer HHI (Heinrich Hertz Institute)
  • Fujitsu
  • Gemtek Technology
  • GENEViSiO
  • GenXComm
  • Gigamon
  • GigaTera Communications
  • Globe Telecom
  • Google
  • Groundhog Technologies
  • Guavus
  • HCL Technologies
  • Helios (Fujian Helios Technologies)
  • HFR Networks
  • Highstreet Technologies
  • Hitachi
  • Hitachi Kokusai Electric
  • Hitachi Vantara
  • HPE (Hewlett Packard Enterprise)
  • HSC (Hughes Systique Corporation)
  • Huawei
  • IBM
  • iBwave Solutions
  • iConNext
  • Infinera
  • Infosys
  • InfoVista
  • Inmanta
  • Innovile
  • InnoWireless
  • Intel Corporation
  • InterDigital
  • Intracom Telecom
  • Inventec Corporation
  • ISCO International
  • IS-Wireless
  • ITRI (Industrial Technology Research Institute, Taiwan)
  • JMA Wireless
  • JRC (Japan Radio Company)
  • Juniper Networks
  • KDDI Corporation
  • Key Bridge Wireless
  • Keysight Technologies
  • Kleos
  • KMW
  • KPN
  • Kumu Networks
  • Kuzey Kibris Turkcell
  • Kyivstar
  • Lemko Corporation
  • Lenovo
  • Lextrum
  • Liberty Global
  • life:)/BeST (Belarusian Telecommunications Network)
  • lifecell Ukraine
  • Lime Microsystems
  • Linux Foundation
  • LIONS Technology
  • LITE-ON Technology Corporation
  • LS telcom
  • LTT (Libya Telecom & Technology)
  • LuxCarta
  • MantisNet
  • Marvell Technology
  • Mavenir
  • MegaFon
  • Meta Connectivity
  • MicroNova
  • Microsoft Corporation
  • MikroTik
  • MitraStar Technology
  • MYCOM OSI
  • Nash Technologies
  • NEC Corporation
  • Net AI
  • Netcracker Technology
  • NETSCOUT Systems
  • Netsia
  • New H3C Technologies
  • New Postcom Equipment
  • Nextivity
  • NGMN Alliance
  • Node-H
  • Nokia
  • NTT DoCoMo
  • NuRAN Wireless
  • Nutaq Innovation
  • NXP Semiconductors
  • Oceus Networks
  • Omnitele
  • ONF (Open Networking Foundation)
  • OnGo Alliance
  • Ooredoo
  • Ooredoo Algeria
  • Ooredoo Tunisia
  • Opanga Networks
  • Openet
  • Opticoms
  • Optus (Singtel)
  • O-RAN Alliance
  • Orange
  • Orange Spain
  • OSA (OpenAirInterface Software Alliance)
  • P.I. Works
  • Parallel Wireless
  • Phluido
  • Picocom
  • Pivotal Commware
  • PLDT
  • Polte
  • Potevio
  • QNAP Systems
  • Qualcomm
  • Quanta Computer
  • Qucell Networks
  • RADCOM
  • Radisys
  • Rakuten Mobile
  • Rakuten Symphony
  • Ranplan Wireless
  • Red Hat
  • RED Technologies
  • Redline Communications
  • Reliance Industries
  • RIMEDO Labs
  • Rivada Networks
  • Rohde & Schwarz
  • Ruijie Networks
  • RunEL
  • SageRAN (Guangzhou SageRAN Technology)
  • Saguna Networks
  • Samji Electronics
  • Samsung
  • Sandvine
  • SCF (Small Cell Forum)
  • Sercomm Corporation
  • Shyam Group
  • Signalwing
  • Siklu
  • Singtel
  • SIRADEL
  • SK Telecom
  • Skyvera (TelcoDR)
  • Smart Communications
  • Smartfren
  • SOLiD
  • Sooktha
  • Spectrum Effect
  • SSC (Shared Spectrum Company)
  • Star Solutions
  • STC (Saudi Telecom Company)
  • STL (Sterlite Technologies Ltd.)
  • Subex
  • Sunwave Communications
  • Systemics-PAB
  • T&W (Shenzhen Gongjin Electronics)
  • Tarana Wireless
  • TCS (Tata Consultancy Services)
  • Tech Mahindra
  • Tecore Networks
  • Telecom Argentina
  • Telefónica Germany
  • Telefónica Group
  • Telkomsel
  • Telrad Networks
  • Telstra
  • TEOCO
  • Thales
  • ThinkRF
  • TI (Texas Instruments)
  • TietoEVRY
  • TIM (Telecom Italia Mobile)
  • TIM Brasil
  • TIP (Telecom Infra Project)
  • TPG Telecom
  • Trópico
  • TSDSI (Telecommunications Standards Development Society, India)
  • Tsinghua Unigroup
  • TTA (Telecommunications Technology Association, South Korea)
  • TTC (Telecommunication Technology Committee, Japan)
  • TTG International
  • Tupl
  • Turkcell
  • ULAK Communication
  • Unizyx Holding Corporation
  • Vasona Networks
  • Vavitel (Shenzhen Vavitel Technology)
  • Verizon Communications
  • VEON
  • VHT (Viettel High Tech)
  • Vi (Vodafone Idea)
  • VIAVI Solutions
  • Virgin Media O2
  • VMware
  • VNC (Virtual NetCom)
  • VNL (Vihaan Networks Limited)
  • Vodafone Germany
  • Vodafone Group
  • Vodafone Ireland
  • Vodafone Italy
  • Vodafone Türkiye
  • WBA (Wireless Broadband Alliance)
  • WDNA (Wireless DNA)
  • WebRadar
  • Wind River Systems
  • WInnForum (Wireless Innovation Forum)
  • Wipro
  • Wireless Telecom Group
  • Wistron Corporation
  • Wiwynn
  • WNC (Wistron NeWeb Corporation)
  • XCOM Labs
  • Xingtera
  • Zain Group
  • Zain Saudi Arabia (Zain KSA)
  • ZaiNar
  • Z-Com
  • Zeetta Networks
  • ZTE
  • Zyxel

COUNTRIES 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