RAN Automation, SON, RIC, xApps & rApps in the 5G Era: Opportunities, Challenges, Strategies & Forecasts

Dublin, Feb. 03, 2025 (GLOBE NEWSWIRE) -- The "RAN Automation, SON, RIC, xApps & rApps in the 5G Era: 2024 - 2030 - Opportunities, Challenges, Strategies & Forecasts" report from SNS Telecom & IT has been added to * ResearchAndMarkets.com's* offering.

Automation of the RAN (Radio Access Network) - the most expensive, technically complex and power-intensive part of cellular infrastructure - is a key aspect of mobile operators' digital transformation strategies aimed at reducing their TCO (Total Cost of Ownership), improving network quality and achieving revenue generation targets. In conjunction with AI (Artificial Intelligence) and ML (Machine Learning), RAN automation has the potential to significantly transform mobile network economics by reducing the OpEx (Operating Expenditure)-to-revenue ratio, minimizing energy consumption, lowering CO2 (Carbon Dioxide) emissions, deferring avoidable CapEx (Captial Expenditure), optimizing performance, improving user experience and enabling new services.

The RAN automation market traces its origins to the beginning of the LTE era when SON (Self-Organizing Network) technology was introduced to reduce cellular network complexity through self-configuration, self-optimization and self-healing. While embedded D-SON (Distributed SON) capabilities such as ANR (Automatic Neighbor Relations) have become a standard feature in RAN products, C-SON (Centralized SON) solutions that abstract control from edge nodes for network-wide actions have been adopted by less than a third of world's approximately 800 national mobile operators due to constraints associated with multi-vendor interoperability, scalability and latency.

These shortcomings, together with the cellular industry's shift towards open interfaces, common information models, virtualization and software-driven networking, are driving a transition from the traditional D-SON and C-SON approach to Open RAN automation with standards-based components - specifically the Near-RT (Real-Time) and Non-RT RICs (RAN Intelligent Controllers), SMO (Service Management & Orchestration) framework, xApps (Extended Applications) and rApps (RAN Applications) - that enable greater levels of RAN programmability and automation.

Along with the ongoing SON to RIC transition, RAN automation use cases have also evolved over the last decade. For example, relatively basic MLB (Mobility Load Balancing) capabilities have metamorphosed into more sophisticated policy-guided traffic steering applications that utilize AI/ML-driven optimization algorithms to efficiently adapt to peaks and troughs in network load and service usage by dynamically managing and redistributing traffic across radio resources and frequency layers.

Due to the much higher density of radios and cell sites in the 5G era, energy efficiency has emerged as one of the most prioritized use cases of RAN automation as forward-thinking mobile operators push ahead with sustainability initiatives to reduce energy consumption, carbon emissions and operating costs without degrading network quality. Some of the other use cases that have garnered considerable interest from the operator community include network slicing enablement, application-aware optimization and anomaly detection.

While the benefits of SON-based RAN automation in live networks are well-known, expectations are even higher with the RIC, SMO and x/rApps approach. For example, Japanese brownfield operator NTT DoCoMo expects to lower its TCO by up to 30% and decrease power consumption at base stations by as much as 50% using Open RAN automation. It is worth highlighting that domestic rival Rakuten Mobile has already achieved approximately 17% energy savings per cell in its live network using RIC-hosted RAN automation applications. Following successful lab trials, the greenfield operator aims to increase savings to 25% with more sophisticated AI/ML models.

Although Open RAN automation efforts seemingly lost momentum beyond the field trial phase for the past couple of years, several commercial engagements have emerged since then, with much of the initial focus on the SMO, Non-RT RIC and rApps for automated management and optimization across Open RAN, purpose-built and hybrid RAN environments. Within the framework of its five-year $14 Billion Open RAN infrastructure contract with Ericsson, AT&T is adopting the Swedish telecommunications giant's SMO and Non-RT RIC solution to replace two legacy C-SON systems. In neighboring Canada, Telus has also initiated the implementation of an SMO and RIC platform along with its multi-vendor Open RAN deployment to transform up to 50% of its RAN footprint and swap out Huawei equipment from its 4G/5G network.

Similar efforts are also underway in other regions. For example, in Europe, Swisscom is deploying an SMO and Non-RT RIC platform to provide multi-technology network management and automation capabilities as part of a wider effort to future-proof its brownfield mobile network, while Deutsche Telekom is progressing with plans to develop its own vendor-independent SMO framework. Open RAN automation is also expected to be introduced as part of Vodafone Group's global tender for refreshing 170,000 cell sites.

Deployments of newer generations of proprietary SON-based RAN automation solutions have not stalled either. In its pursuit of achieving L4 (Highly Autonomous Network) operations, China Mobile has recently initiated the implementation of a hierarchical RAN automation platform and an associated digital twin system, starting with China's Henan province. Among other interesting examples, SoftBank is implementing a closed loop automation solution for cluster-wide RAN optimization in stadiums, event venues, and other strategic locations across Japan, which supports data collection and parameter tuning in 1-5 minute intervals as opposed to the 15-minute control cycle of traditional C-SON systems. It should be noted that the Japanese operator eventually plans to adopt RIC-hosted centralized RAN optimization applications in the future.

In addition, with the support of several mobile operators, including SoftBank, Vodafone, Bell Canada and Viettel, the idea of hosting third party applications for real-time intelligent control and optimization - also referred to as dApps (Distributed Applications) - directly within RAN baseband platforms is beginning to gain traction. As a counterbalance to this approach, Ericsson, Nokia, Huawei and other established RAN vendors are making considerable progress with a stepwise approach towards embedding AI and ML functionalities deeper into their DU (Distributed Unit) and CU (Centralized Unit) products in line with the 3GPP's long-term vision of an AI/ML-based air interface in the 6G era.

Global spending on RIC, SMO and x/rApps is forecast to grow at a CAGR of more than 125% between 2024 and 2027 alongside the second wave of Open RAN infrastructure rollouts by brownfield operators. The Open RAN automation market will eventually account for nearly $700 Million in annual investments by the end of 2027 as standardization gaps and technical challenges in terms of the SMO-to-Non-RT RIC interface, application portability across RIC platforms and conflict mitigation between x/rApps are ironed out. The wider RAN automation software and services market - which includes Open RAN automation, RAN vendor SON solutions, third party C-SON platforms, baseband-integrated intelligent RAN applications, RAN planning and optimization software, and test/measurement solutions - is expected to grow at a CAGR of approximately 8% during the same period.

The report presents an in-depth assessment of the RAN automation 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 RAN and end-to-end mobile network automation from 2024 to 2030. The forecasts cover three network domains, nine functional areas, three access technologies and five regional markets.

The report comes with an associated Excel datasheet suite covering quantitative data from all numeric forecasts presented in the report.

*Key Topics Covered:*

*Chapter 1: Introduction*

*Chapter 2: An Overview of RAN Automation*

· What is RAN Automation?
· Levels of Automation in Intelligent RAN Implementations
· Functional Areas of RAN Automation
· RAN Automation Value Chain
· Market Drivers

· Growing Complexity of RAN in the 5G Era
· Open RAN & vRAN (Virtualized RAN) Adoption
· TCO (Total Cost of Ownership) Reduction
· Energy Savings, Sustainability & Environmental Conservation
· Popularity of Both Operational & Generative AI Technologies
· Subscriber Experience & Network Performance Benefits
· Network Slicing & New Revenue-Generating Opportunities
· Proliferation of Shared Spectrum, Private 5G & Neutral Host Networks

· Market Barriers

· Service Provider Revenue Stagnation & Cost-Cutting Measures
· Slow Pace of Brownfield RAN Reinvestment Cycles
· Implementation-Related Technical Challenges
· Standardization Gaps & Multi-Vendor Interoperability
· Conflict Mitigation Between x/rApps
· Dominance of Incumbent RAN Vendors
· Conservatism & Trust in Automation
· Network Security & Privacy Concerns

*Chapter 3: RAN Automation Technology, Architecture & Use Cases*

· Traditional SON Solutions
· Open Specifications-Based RIC, SMO, xApps & rApps
· AI-Native RAN Infrastructure
· RAN Planning & Optimization
· Test & Measurement Solutions
· Automation & Intelligence Beyond the RAN
· Network Automation Use Cases

*Chapter 4: Key Trends in Intelligent RAN Implementations*

· Transition From SON to Open RAN-Based RIC, SMO, xApps & rApps
· Moving Closer to Higher Levels of Automation
· Operational AI & ML
· Gen AI (Generative AI)
· Network Data Analytics
· Observability of Network Operations
· Cloud-Native & Software-Centric Networking
· Other Trends & Developments

*Chapter 5: Standardization & Collaborative Initiatives*

· 3GPP (Third Generation Partnership Project)
· AI-RAN Alliance
· ETSI (European Telecommunications Standards Institute)
· GSMA (GSM Association)
· GTAA (Global Telco AI Alliance)
· IETF (Internet Engineering Task Force)
· ITU (International Telecommunication Union)
· Linux Foundation
· NGMN Alliance
· ONF (Open Networking Foundation)
· O-RAN Alliance
· OSA (OpenAirInterface Software Alliance)
· OSSii (Operations Support Systems Interoperability Initiative)
· SCF (Small Cell Forum)
· TIP (Telecom Infra Project)
· TM Forum
· Other Initiatives & Academic Research

*Chapter 6: RAN Automation Case Studies*

· AT&T
· Bell Canada
· Bharti Airtel
· BT Group
· DT (Deutsche Telekom)
· Elisa
· Globe Telecom
· NTT DoCoMo
· Ooredoo
· Orange
· Rakuten Mobile
· Singtel
· SK Telecom
· STC (Saudi Telecom Company)
· Telecom Argentina
· Telefonica Group
· TIM (Telecom Italia Mobile)
· Turkcell
· Verizon Communications
· Vodafone Group

*Other Recent Deployments & Ongoing Projects*

· 1&1: Highly Automated Control of Europe's First Greenfield Open RAN Network
· 4iG Group: Closed Loop Network Management & Customer Experience Monitoring
· America Movil: SON-Based RAN Automation for 5G Network Rollout & Optimization
· Andorra Telecom: Doubling Throughput With Automated RF Interference Mitigation
· Axiata Group: Autonomous Network Initiative for Streamlining Operations
· Batelco: AI-Powered Energy Savings & Carbon Footprint Reduction
· beCloud (Belarusian Cloud Technologies): AI-Enabled Network Management
· Beeline Russia (VimpelCom): Transforming the Mobile Experience Using C-SON
· BTC (Botswana Telecommunications Corporation): Nationwide Network Optimization
· C Spire: SON-Enabled Automation of Regional Wireless Network
· Cellfie Mobile: Intelligent RAN Monitoring & Management
· CETIN Group: Multi-Domain Automated Network Optimization
· China Mobile: Aiming for AI/ML-Assisted L4 Automation by 2025
· China Telecom: Co-Governance of Shared 5G Network Infrastructure
· China Unicom: CUBE-RAN Intelligent Open Platform
· CK Hutchison: Accelerating the Journey Towards Fully Automated RAN Operations
· DIGI Communications: Laying the Groundwork for Zero-Touch Automation
· DISH Network Corporation: RIC-Based RAN Programmability & Intelligence
· Djezzy: Harnessing C-SON for Automated RAN Optimization & Management
· Etisalat Group (e&): AI/ML-Enabled Intelligent Network Management Platform
· FET (Far EasTone Telecommunications): Advancing Sustainability Goals With ML-Driven RAN Automation
· KDDI: Moving Towards RIC-Based Automation for Network Slicing Enablement
· KPN: Replacing Labor-Intensive RAN Optimization Tools With SON-Based Automation
· KT Corporation: Embracing Intelligent Control of RAN Resources & Operations
· LG Uplus: Evaluating the RIC Approach for Vendor-Independent RAN Automation
· Liberty Global: Building a Customer-First 5G Network Using Autonomous Optimization Decisions
· LTT (Libya Telecom & Technology): Nationwide RAN Automation for Enhanced Network Quality
· MASMOVIL: Improving Customer Experience During Peak Hours With ML-Assisted Optimization
· MegaFon: Delivering an Exemplary Subscriber Experience Through SON Technology
· MEO (Altice Portugal): Automated RAN Optimization & Service Assurance
· MTN Group: Pioneering Autonomous Mobile Networks in Africa
· MTS (Mobile TeleSystems): Self-Adjusting Intelligent Network
· Odido: AI-Driven Cell Site Energy Management Solution
· Reliance Jio Infocomm: Improving Customer Experience With C-SON
· Rogers Communications: Cross-Domain Service Orchestration & Automation
· Smart Communications (PLDT): Planning the SON-to-RIC Transition
· Smartfren: Automating Heterogenous Network Management
· SoftBank Group: Spearheading AI/ML-Driven Advancements in the RAN
· Swisscom: Future-Proofing Brownfield Mobile Network With SMO & Non-RT RIC
· TDC NET: Inching Towards Net Zero Goals With RAN Automation
· Telia Company: Setting the Foundation for Zero-Touch Mobile Networks
· Telkomsel: Autonomous Network Program for Operational Efficiency
· Telstra: Advancing Mobile Network Automation Capabilities
· Telus: SMO & RIC-Based RAN Network Intelligence Platform
· TPG Telecom: Managing Peak Traffic Congestion With C-SON
· Turk Telekom: Driving Efficiency Through Network Automation
· Ucom (Armenia): AI Functionalities for Mobile Network Modernization
· VEON: Leveraging C-SON to Enhance Network Performance
· Viettel Group: AI/ML-Enabled Physical Layer Signal Processing
· Zain Group: Targeting L4 Automation for Efficient 5G Network Operations

*Chapter 7: Key Ecosystem Players*

· A10 Networks
· A5G Networks
· Aalyria
· Aarna Networks
· Abside Networks
· Accedian
· Accelleran
· Accuver (InnoWireless)
· Acentury
· Actiontec Electronics
· Adtran
· Aglocell
· AI-LINK
· Aira Technologies
· AirHop Communications
· Airspan Networks
· AiVader
· Aliniant
· Allot
· Alpha Networks
· Amazon/AWS (Amazon Web Services)
· AMD (Advanced Micro Devices)
· Amdocs
· Anktion (Fujian) Technology
· Anritsu
· Antevia Networks
· Arcadyan Technology Corporation (Compal Electronics)
· Argela
· Arm
· ArrayComm (Chengdu ArrayComm Wireless Technologies)
· Arrcus
· Artemis Networks
· Artiza Networks
· Arukona
· AsiaInfo Technologies
· Askey Computer Corporation (ASUS - ASUSTeK Computer)
· ASOCS
· Aspire Technology (NEC Corporation)
· ASTRI (Hong Kong Applied Science and Technology Research Institute)
· Ataya
· ATDI
· Atesio
· Atrinet (ServiceNow)
· Auray Technology (Auden Techno)
· Aviat Networks
· Azcom Technology
· Baicells
· Betacom
· BLiNQ Networks (CCI - Communication Components Inc.)
· Blu Wireless
· Booz Allen Hamilton
· BravoCom
· Broadcom
· BTI Wireless
· BubbleRAN
· B-Yond/Reailize
· C3Spectra
· CableFree (Wireless Excellence)
· Cambium Networks
· Capgemini Engineering
· CBNG (Cambridge Broadband Networks Group)
· Celfinet (Cyient)
· Celona
· CelPlan Technologies
· Ceragon Networks
· CGI
· Chengdu NTS
· CICT - China Information and Communication Technology Group (China Xinke Group)
· Ciena Corporation
· CIG (Cambridge Industries Group)
· Cisco Systems
· Clavister
· Cohere Technologies
· Comarch
· Comba Telecom
· CommAgility (E-Space)
· CommScope
· Compal Electronics
· COMSovereign
· Contela
· Corning
· Creanord
· Cyient
· DeepSig
· Dell Technologies
· DGS (Digital Global Systems)
· Digis Squared
· Digitata
· D-Link Corporation
· Druid Software
· DZS
· ECE (European Communications Engineering)
· EDX Wireless
· eino
· Elisa Polystar
· Encora
· Equiendo
· Ericsson
· Errigal
· ETRI
· EXFO
· F5
· Fairspectrum
· Federated Wireless
· Firecell
· Flash Networks
· Forsk
· Fortinet
· Foxconn
· Fraunhofer HHI
· Fujitsu
· FullRays
· Future Connections
· FYRA
· G REIGNS
· Gemtek Technology
· GENEViSiO
· Gigamon
· GigaTera Communications
· GlobalLogic
· Globalstar
· Groundhog Technologies
· Guavus
· GXC
· HCLTech
· Helios
· HFR Networks
· Highstreet Technologies
· Hitachi
· HPE
· HSC
· Huawei
· IBM
· iBwave Solutions
· iConNext
· Infinera
· Infosys
· Infovista
· Inmanta
· Innovile
· InnoWireless
· Intel Corporation
· InterDigital
· Intracom Telecom
· Inventec Corporation
· ISCO International
· IS-Wireless
· Itential
· ITRI
· JMA Wireless
· JRC
· Juniper Networks
· Key Bridge Wireless
· Keysight Technologies
· Kleos
· KMW
· Kumu Networks
· Lemko Corporation
· Lenovo
· Lime Microsystems
· LIONS Technology
· LITE-ON Technology
· LitePoint
· LS telcom
· LuxCarta
· MantisNet
· Marvell Technology
· Mavenir
· Maxar Technologies
· Meta
· MicroNova
· Microsoft Corporation
· MikroTik
· MitraStar Technology
· Mobileum
· MosoLabs
· MYCOM OSI
· Nash Technologies
· NEC
· Net AI
· Netcracker Technology
· NETSCOUT Systems
· Netsia
· Neutroon Technologies
· New H3C Technologies
· New Postcom Equipment
· Nextivity
· Node-H
· Nokia
· Novowi
· NuRAN Wireless
· NVIDIA
· NXP Semiconductors
· Oceus Networks
· Omnitele
· OneLayer
· Ookla
· Opanga Networks
· OREX (NTT DoCoMo)
· P.I. Works
· Palo Alto Networks
· Parallel Wireless
· Pente Networks
· Phluido
· Picocom
· Pivotal Commware
· Potevio
· QCT
· Qualcomm
· Quanta Computer
· Qucell Networks
· RADCOM
· Radisys
· Radware
· Rakuten Symphony
· Ranlytics
· Ranplan Wireless
· Rebaca Technologies
· Red Hat (IBM)
· RED Technologies
· REPLY
· RIMEDO Labs
· Rivada Networks
· Rohde & Schwarz
· Ruijie Networks
· RunEL
· SageRAN
· Samji Electronics
· Samsung
· Sandvine
· Sercomm Corporation
· ServiceNow
· Shabodi
· Signalwing
· SIRADEL
· Skyvera
· SOLiD
· Sooktha
· Spectrum Effect
· Spirent Communications
· SRS
· SSC
· Star Solutions
· Subex
· Sunwave Communications
· Supermicro
· SynaXG Technologies
· Systemics-PAB
· T&W
· Tarana Wireless
· TCS
· Tech Mahindra
· Tecore Networks
· TECTWIN
· Telrad Networks
· TEOCO/Aircom
· ThinkRF
· TietoEVRY
· Tropico
· TTG International
· Tupl
· ULAK Communication
· Vavitel
· VHT
· VIAVI Solutions
· VMware
· VNL - Vihaan Networks
· Wave Electronics
· WDNA
· WIM Technologies
· Wind River Systems
· Wipro
· Wiwynn
· WNC
· Xingtera
· ZaiNar
· Z-Com
· Zeetta Networks
· Zinkworks
· ZTE
· zTouch Networks
· Zyxel

*Chapter 8: Market Sizing & Forecasts*

· Mobile Network Automation
· Network Domain Submarkets
· RAN Automation Functional Areas
· SON-Based Automation Submarkets
· Open RAN Automation Submarkets
· Access Technology Generations
· Regional Segmentation

*Chapter 9: Conclusion & Strategic Recommendations*

· Why is the Market Poised to Grow?
· Future Roadmap: 2024 - 2030
· Reviewing the Real-World Benefits & TCO Savings Potential of RAN Automation
· Impact of Intelligent Automation on RAN Engineering Roles
· Transition From SON to Open RAN Automation
· Evolution of Use Cases & AI/ML Algorithms
· Growing Focus on Energy Efficiency & Sustainability
· Vertical Industries & Private Wireless Automation
· Diversified Community of x/rApp Developers
· Signs of Consolidation in the SMO & RIC Ecosystem
· Which RAN Automation Platform & Application Vendors Are Leading the Market?
· Prospects of Hosting Third Party Applications Within RAN Baseband Products
· Paving the Path to an AI/ML-Based 6G Air Interface
· Convergence of AI & RAN Infrastructure
· Strategic Recommendations

*Chapter 10: Expert Opinion - Interview Transcripts*

· AirHop Communications
· Amdocs
· Groundhog Technologies
· Innovile
· Net AI
· Nokia
· P.I. Works
· Qualcomm
· Rakuten Mobile
· RIMEDO Labs

For more information about this report visit https://www.researchandmarkets.com/r/n51hib

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