Machine Learning (ML) In a 5G Standalone (SA) Self Organizing Network (SON)

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© 2020 by IJCTT Journal
Volume-68 Issue-11
Year of Publication : 2020
Authors : Srinivasan Sridharan
DOI :  10.14445/22312803/IJCTT-V68I11P105

How to Cite?

Srinivasan Sridharan, "Machine Learning (ML) In a 5G Standalone (SA) Self Organizing Network (SON)," International Journal of Computer Trends and Technology, vol. 68, no. 11, pp. 43-48, 2020. Crossref, 10.14445/22312803/IJCTT-V68I11P105

Abstract
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. It was found that 5G intentions revere heterogeneous demands of phrases of data-rate, reliability, latency, or efficiency. Mobile operators shall be in a position in imitation of revere whole of these requirements using shared network infrastructure’s resources. 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.

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Keywords
5G, machine learning (ML), Self-organizing Networks (SONs), 5G Standalone, Artificial Intelligence (AI)