Recent Advancements in Applications of Artificial Intelligence and Machine Learning for 5G Technology: A Review
Alekya Nyalapelli, Shubham Sharma, Pranjal Phadnis, Maithili Patil, Avinash Tandle
Abstract
As the fifth generation (5G) of wireless communication rolls out worldwide, conceptualized use cases and disruptive industry solutions are being deployed to offer smooth, frictionless, and secure connectivity. The landscape of Artificial Intelligence (AI) and Machine Learning (ML) can be seen as potential drivers in the automation and optimization of network performances and management complexities. The shifting network behaviors and complicated modern applications present diverse network performance traffic, which can be exploited by service providers to deal with network demands and provide superior user experiences. The existing research can be divided into the following 5G research areas, which include network traffic, resource allocation, network slicing, mobility management, physical layer security, etc., to name a few. The primary objective of this paper is to provide a comprehensive perspective on the expanding diversity of viable ML-assisted solutions for tackling various 5G network-level issues. The paper concludes with an indepth investigation of the challenges and unexplored directions of future research pertaining to making 5G applications more reliable for future use cases.