A Survey of AI/ML Related Standardization Efforts in 5G Mobile Networks (O-RAN and 3GPP)
DOI:
https://doi.org/10.58445/rars.2309Keywords:
AI/ML, Mobile Networks, 5G, 6G, 3GPP, O-RAN, Standardization, TelecommunicationsAbstract
Using Artificial Intelligence (AI) and Machine Learning (ML) in 5G wireless networks can help
Mobile Network Operators (MNOs) improve their service quality while reducing the costs of
running and optimizing their networks. This paper surveys the ongoing AI/ML related
standardization efforts in Open Radio Access Network (O-RAN) Alliance and the 3rd Generation Partnership Project (3GPP). It highlights the key initiatives aimed at integration and standardization of AI/ML in Radio Access Network (RAN), including the definition of AI/ML
workflows, model training, deployment, inference, and model management. The paper also
provides an overview of some of the important AI/ML use cases, such as traffic steering,
network slicing and RAN slice Service Level Agreement (SLA) assurance, predictive
maintenance, and energy savings. Through the analysis of the current standardization efforts
and potential future directions, this survey provides a detailed overview of how AI/ML can be
applied to 5G RAN and its potential to improve the overall network performance, the quality of user experience, and lowered operational costs.
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