A Review on Machine Learning Algorithms in Smart Communication System

Abstract

Including ML techniques into smart communication systems has fundamentally changed modern wireless networks such that they are now more trustworthy, efficient, and flexible than ever before. Among the many applications of machine learning (ML) discussed in this paper are channel prediction, power allocation, IoT enabled devices, and network automation. This study aims to provide a complete summary of how present achievements in domains like neuro-fuzzy inference systems, clustering approaches, and deep reinforcement learning (DRL) tackle challenges with data processing, security, and resource management. Furthermore, the assessment identifies significant advances and areas where additional research is required, therefore supporting future developments in this subject.

Keywords: ML, Smart communication, DRL, Network automation