Machine Learning (ML) In a 5G Standalone (SA) Self Organizing Network (SON)
This paper addresses the potential benefits of integrating ML into 5G SA SONs for telecommunication service providers, aiming to improve network efficiency and enable new cellular use cases.
This paper provides an overview of the application of machine learning (ML) within 5G Standalone (SA) Self-Organizing Networks (SONs). It highlights how ML in 5G SA SONs can enhance Operations, Administration, and Maintenance (OAM) activities and improve network throughput.
Machine learning (ML) is included in Self-organizing Networks (SONs) that are key drivers for enhancing the Operations, Administration, and Maintenance (OAM) activities. It is included in the 5G Standalone (SA) system is one of the 5G communication tracks that transforms 4G networking to next-generation technology that is based on mobile applications. The research's main aim is to an overview of machine learning (ML) in 5G standalone core networks. 5G Standalone is considered a key enabler by the service providers as it improves the efficacy of the throughput that edges the network. It also assists in advancing new cellular use cases like ultra-reliable low latency communications (URLLC) that supports combinations of frequencies.