SON (Self-Organizing Networks) in the 5G & Open RAN Era: 2022 – 2030 – Opportunities, Challenges, Strategies & Forecasts

SON (Self-Organizing Networks) in the 5G & Open RAN Era: 2022 – 2030 – Opportunities, Challenges, Strategies & Forecasts


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.


Chapter 1: Introduction
Executive Summary
Topics Covered
Forecast Segmentation
Key Questions Answered
Key Findings
Methodology
Target Audience
Companies & Organizations Mentioned
Chapter 2: SON & Mobile Network Optimization Ecosystem
Conventional Mobile Network Optimization
Network Planning
Measurement Collection: Drive Tests, Probes & End User Data
Post-Processing, Optimization & Policy Enforcement
The SON (Self-Organizing Network) Concept
What is SON?
The Need for SON
Functional Areas of SON
Self-Configuration
Self-Optimization
Self-Healing
Self-Protection
Self-Learning
SON Value Chain
SON, xApp/rApp & Automation Specialists
OSS & RIC Platform Providers
RAN, Core & Transport Network Equipment Suppliers
Wireless Service Providers
National Mobile Operators
Fixed-Line Service Providers
Private 4G/5G Network Operators
Neutral Hosts
End Users
Consumers
Enterprises & Vertical Industries
Other Ecosystem Players
Market Drivers
The 5G & Open RAN Era: Continued Infrastructure Investments
Optimization in Complex Multi-RAN Environments
OpEx & CapEx Reduction: The Cost Savings Potential
Improving Subscriber Experience & Churn Reduction
Power Savings: Towards Greener Mobile Networks
Alleviating Congestion With Traffic Management
Enabling Plug & Play Deployment of Small Cells
Growing Adoption of Private 4G/5G Networks
Market Barriers
Complexity of Implementation
Reorganization & Changes to Standard Engineering Procedures
Lack of Trust in Automation
Proprietary SON Algorithms
Coordination Between Distributed & Centralized SON
Network Security Concerns: New Interfaces & Lack of Monitoring
Chapter 3: SON Technology, Implementation Architectures & Use Cases
Where Does SON Sit Within a Mobile Network?
RAN
Mobile Core
Transport (Fronthaul, Midhaul & Backhaul)
Device-Assisted SON
Traditional SON Architecture
D-SON (Distributed SON)
C-SON (Centralized SON)
H-SON (Hybrid SON)
Open Standards-Compliant RIC, xApps & rApps
RIC (RAN Intelligent Controller)
Near-RT (Real-Time) RIC
Non-RT (Real-Time) RIC
xApps: Open D-SON Applications
rApps: Open C-SON Applications
SON Use Cases
RAN-Centric Use Cases
ANR (Automatic Neighbor Relations)
CNR (Centralized Neighbor Relations)
PCI (Physical Cell ID) Allocation & Conflict Resolution
CCO (Coverage & Capacity Optimization)
MRO (Mobility Robustness Optimization)
MLB (Mobility Load Balancing)
RACH (Random Access Channel) Optimization
ICIC (Inter-Cell Interference Coordination) & eICIC (Enhanced ICIC)
COD/COC (Cell Outage Detection & Compensation)
MDT (Minimization of Drive Tests)
Advanced Traffic Steering
Automated Anomaly Detection
Massive MIMO & Beamforming Optimization
4G-5G Dual Connectivity Management
RAN Slice Management
DSS (Dynamic Spectrum Sharing)
Frequency Layer Management
BBU (Baseband Unit) Resource Pooling
Radio Resource Allocation for Complex Vertical Applications
Handover Management in V2X Communications Scenarios
Rapid Plug & Play Configuration of Small Cells
DAS (Distributed Antenna System) Optimization
Multi-Domain, Core & Transport-Related Use Cases
Self-Configuration & Testing of Network Elements
Domain Connectivity Management
Automated Inventory Checks
AIC (Automated Inconsistency Correction)
Self-Healing of Network Faults
Signaling Storm Protection
Energy Efficiency & Savings
QoS & QoE-Based Optimization
Congestion Prediction & Management
AI-Enabled Performance Diagnostics
Industrial IoT Optimization
Core Network Automation
Network Slicing Resource Allocation
Optimization of VNFs & CNFs
Auto-Provisioning of Transport Links
Transport Network Bandwidth Optimization
Wireless Transport Interference Management
Seamless Vendor Infrastructure Swap
SON Coordination Management
Cognitive & Self-Learning Networks
Chapter 4: Key Trends in Next-Generation SON Implementations
Open RAN & vRAN (Virtualized RAN) Architectures
Enabling RAN Automation & Intelligence With RIC, xApps & rApps
Small Cells, HetNets & RAN Densification
Plug & Play Small Cells
SON-Enabled Coordination of UDNs (Ultra-Dense Networks)
Shared & Unlicensed Spectrum
Dynamic Management of Spectrum Using SON
MEC (Multi-Access Edge Computing)
Potential Synergies With SON
Network Slicing
SON Mechanisms for Network Slicing in 5G Networks
Big Data & Advanced Analytics
Maximizing the Benefits of SON With Big Data
The Importance of Predictive & Behavioral Analytics
AI (Artificial Intelligence) & ML (Machine Learning)
Towards Self-Learning SON Engines
Deep Learning: Enabling Zero-Touch Mobile Networks
NFV (Network Functions Virtualization)
Enabling SON-Driven Deployment of VNFs & CNFs
SDN (Software-Defined Networking) & Programmability
Using the SDN Controller as a Platform for SON in Transport Networks
Cloud Computing
Facilitating C-SON Scalability & Elasticity
Other Trends & Complementary Technologies
Private 4G/5G Networks
FWA (Fixed Wireless Access)
DPI (Deep Packet Inspection)
Digital Security for Self-Protection
SON Capabilities for IoT Applications
User-Based Profiling & Optimization for Vertical 5G Applications
Addressing D2D (Device-to-Device) Communications & New Use Cases
Chapter 5: Standardization, Regulatory & Collaborative Initiatives
3GPP (Third Generation Partnership Project)
3GPP Standardization of SON Capabilities
LTE SON Features
Release 8
Release 9
Release 10
Release 11
Release 12
Releases 13 & 14
5G NR SON Features
Release 15
Release 16
Release 17
Release 18 & Beyond
Implementation Approach for 3GPP-Specified SON Features
O-RAN Alliance
Open RAN RIC Architecture Specifications
xApp & rApp Use Cases
OSA (OpenAirInterface Software Alliance)
M5G (MOSAIC5G) Project: Flexible RAN & Core Controllers
TIP (Telecom Infra Project)
RIA (RAN Intelligence & Automation) Project
ONF (Open Networking Foundation)
SD-RAN Project: Near Real-Time RIC & Exemplar xApps
Linux Foundation's ONAP (Open Network Automation Platform)
OOF (ONAP Optimization Framework)-SON for 5G Networks
Interface Support for Open RAN RIC Integration
SCF (Small Cell Forum)
4G/5G Small Cell SON & Orchestration
OSSii (Operations Support Systems Interoperability Initiative)
Enabling Multi-Vendor SON Interoperability
NGMN Alliance
Conception of the SON Initiative
Recommendations for Multi-Vendor SON Deployment
SON Capabilities for 5G Network Deployment, Operation & Management
Others
Chapter 6: SON Deployment Case Studies
AT&T
Vendor Selection
SON Deployment Review
Results & Future Plans
Bell Canada
Vendor Selection
SON Deployment Review
Results & Future Plans
Bharti Airtel
Vendor Selection
SON Deployment Review
Results & Future Plans
BT Group
Vendor Selection
SON Deployment Review
Results & Future Plans
China Mobile
Vendor Selection
SON Deployment Review
Results & Future Plans
Elisa
Vendor Selection
SON Deployment Review
Results & Future Plans
Globe Telecom
Vendor Selection
SON Deployment Review
Results & Future Plans
KDDI Corporation
Vendor Selection
SON Deployment Review
Results & Future Plans
MegaFon
Vendor Selection
SON Deployment Review
Results & Future Plans
NTT DoCoMo
Vendor Selection
SON Deployment Review
Results & Future Plans
Ooredoo
Vendor Selection
SON Deployment Review
Results & Future Plans
Orange
Vendor Selection
SON Deployment Review
Results & Future Plans
Singtel
Vendor Selection
SON Deployment Review
Results & Future Plans
SK Telecom
Vendor Selection
SON Deployment Review
Results & Future Plans
Telecom Argentina
Vendor Selection
SON Deployment Review
Results & Future Plans
Telefónica Group
Vendor Selection
SON Deployment Review
Results & Future Plans
TIM (Telecom Italia Mobile)
Vendor Selection
SON Deployment Review
Results & Future Plans
Turkcell
Vendor Selection
SON Deployment Review
Results & Future Plans
Verizon Communications
Vendor Selection
SON Deployment Review
Results & Future Plans
Vodafone Group
Vendor Selection
SON Deployment Review
Results & Future Plans
Other Recent Deployments & Ongoing Projects
beCloud (Belarusian Cloud Technologies): AI-Enabled Network Automation & Performance Management
Beeline Russia: Transforming the Mobile Experience Using C-SON Technology
Betacom: Accelerating Enterprise Private 5G Adoption With RAN Automation
BTC (Botswana Telecommunications Corporation): SON for Nationwide Network Optimization
Celona: Self-Organizing 5G LAN Solution for Enterprises
América Móvil: Accelerating 5G Rollouts Through SON-Based Automation
DISH Network Corporation: RIC-Based Custom RAN Programmability & Intelligence
DT (Deutsche Telekom): Berlin SD-RAN 4G/5G Outdoor Field Trial
KPN: SON-Driven Automation for Network Optimization
Kyivstar: Leveraging C-SON to Enhance Network Performance
Liberty Global: Building a Customer-First Network
LTT (Libya Telecom & Technology): Nationwide RAN Automation
NEC Corporation: Self-Learning Local 5G Networks
Opticoms: Optimizing Open RAN-Compliant Private 5G Networks
Rakuten Mobile: Embedded RIC for RAN Automation Applications
Smart Communications (PLDT): Enabling Multi-Vendor 4G/5G Network Automation
Smartfren: Facilitating Network Densification & HetNet Management With C-SON Technology
STC (Saudi Telecom Company): Automating Network Operations & Driving 5G Transformation
Telkomsel: SON-Enabled Automated Network Optimization
Telstra: Boosting Mobile Network Automation
Zain Group: SON for Performance Enhancement
Chapter 7: Key Ecosystem Players
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
Node-H
Nokia
NuRAN Wireless
NXP Semiconductors
Oceus Networks
Omnitele
Opanga Networks
Openet (Amdocs)
P.I. Works
Parallel Wireless
Phluido
Picocom
Pivotal Commware
Polte
Potevio (CETC – China Electronics Technology Group Corporation)
Qualcomm
Quanta Computer
Qucell Networks (InnoWireless)
RADCOM
Radisys (Reliance Industries)
Rakuten Symphony
Ranplan Wireless
Red Hat (IBM)
RED Technologies
RIMEDO Labs
Rivada Networks
Rohde & Schwarz
Ruijie Networks
RunEL
SageRAN (Guangzhou SageRAN Technology)
Saguna Networks (COMSovereign)
Samji Electronics
Samsung
Sandvine
Sercomm Corporation
Signalwing
Siklu
SIRADEL
Skyvera (TelcoDR)
SOLiD
Sooktha
Spectrum Effect
SSC (Shared Spectrum Company)
Star Solutions
STL (Sterlite Technologies Ltd.)
Subex
Sunwave Communications
Systemics-PAB
T&W (Shenzhen Gongjin Electronics)
Tarana Wireless
TCS (Tata Consultancy Services)
Tech Mahindra
Tecore Networks
Telrad Networks
TEOCO
ThinkRF
TI (Texas Instruments)
TietoEVRY
Trópico (CPQD – Center for Research and Development in Telecommunications, Brazil)
TTG International
Tupl
ULAK Communication
Vavitel (Shenzhen Vavitel Technology)
VHT (Viettel High Tech)
VIAVI Solutions
VMware
VNC – Virtual NetCom (COMSovereign)
VNL – Vihaan Networks Limited (Shyam Group)
WDNA (Wireless DNA)
WebRadar
Wind River Systems
Wipro
Wiwynn (Wistron Corporation)
WNC (Wistron NeWeb Corporation)
XCOM Labs
Xingtera
ZaiNar
Z-Com
Zeetta Networks
ZTE
Zyxel (Unizyx Holding Corporation)
Chapter 8: Market Sizing & Forecasts
SON & Mobile Network Optimization Revenue
SON Revenue
SON Revenue by Network Segment
RAN
Mobile Core
Transport (Fronthaul, Midhaul & Backhaul)
RAN Segment SON Revenue by Architecture: Traditional SON vs. Open RAN RIC, xApps & rApps
Traditional D-SON & C-SON
Embedded D-SON Features
Third Party C-SON & OSS Platforms
Open RAN RIC, xApps & rApps
RIC Platforms
Near Real-Time xApps
Non Real-Time rApps
Mobile Operators' In-House SON Tools & Systems
SON Revenue by Access Network Technology
2G & 3G
LTE
5G NR
Wi-Fi & Others
SON Revenue by Region
Conventional Mobile Network Planning & Optimization Revenue
Conventional Mobile Network Planning & Optimization Revenue by Region
North America
SON
Conventional Mobile Network Planning & Optimization
Asia Pacific
SON
Conventional Mobile Network Planning & Optimization
Europe
SON
Conventional Mobile Network Planning & Optimization
Middle East & Africa
SON
Conventional Mobile Network Planning & Optimization
Latin & Central America
SON
Conventional Mobile Network Planning & Optimization
Chapter 9: Conclusion & Strategic Recommendations
Why is the Market Poised to Grow?
Future Roadmap: 2022 – 2030
2022 – 2025: Transition From Traditional SON to RIC Platforms, xApps & rApps
2026 – 2029: Commercial Maturity of Advanced AI/ML-Based SON Implementations
2030 & Beyond: Towards Zero-Touch 5G & 6G Network Automation
Competitive Industry Landscape: Acquisitions, Alliances & Consolidation
The C-SON Versus D-SON Debate
Evaluating the Practical Benefits of SON
Prospects of Open RAN Standards-Compliant RIC Platforms, xApps & rApps
End-to-End SON: From the RAN to the Core & Transport Domains
Growing Adoption of SON Capabilities for Wi-Fi & Non-3GPP Access Technologies
The Importance of AI & ML-Driven SON Algorithms
Improving End User Experience With QoE-Based Optimization
Enabling Network Slicing & Advanced 5G Capabilities
Greater Focus on Self-Protection
Addressing IoT Optimization
Managing Shared & Unlicensed Spectrum
Easing the Deployment of Private 4G/5G Networks
Assessing the Impact of SON on Optimization & Field Engineers
Strategic Recommendations
SON Solution Providers
Mobile Operators
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)

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