Authors : Manish Kumar

Volume/Issue : Volume 10 - 2025, Issue 9 - September

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Google Scholar : https://tinyurl.com/4tp5ue2j

Scribd : https://tinyurl.com/ajvb39sn

DOI : https://doi.org/10.38124/ijisrt/25sep051

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Abstract : Fifth-generation (5G) mobile networks introduce unprecedented performance requirements including enhanced mobile broadband (eMBB), ultra-reliable low-latency communications (URLLC), and massive machine-type communications (mMTC). These requirements demand highly adaptive, automated, and intelligent management. Artificial Intelligence (AI) and Machine Learning (ML) have emerged as essential enablers for 5G system deployment, installation, configuration, and optimization. This paper explores the integration of AI/ML with 3GPP-defined network functions and management frameworks, focusing on specifications 3GPP TS 28.104, 3GPP TS 28.105, and 3GPP TR 29.908, while also analyzing how AI-driven analytics enhance deployment, coverage, sustainability, energy efficiency, and user experience.

Keywords : 5G Networks, Artificial Intelligence (AI), Machine Learning (ML), Network Data Analytics Function (NWDAF), 3GPP Standards, Network Slicing, Coverage Optimization, Traffic and Mobility Optimization, Energy Efficiency

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