Review of Machine Learning Applications in Wireless Communications

TL;DR

This review explores how machine learning techniques are applied to enhance 5G and millimeter wave wireless communication systems, highlighting recent research, benefits, and implementation challenges.

Contribution

It provides a comprehensive overview of ML applications in wireless communications, including summaries of recent studies and analysis of integration and implementation aspects.

Findings

ML improves wireless communication efficiency

RSS-based classification aids indoor mmWave network management

ML techniques are increasingly adopted in 5G technologies

Abstract

This paper looks at various aspects of Machine Learning (ML) applications in wireless communication technologies, focusing mainly on fifth-generation (5G) and millimeter wave (mmWave) technologies. This paper includes the summaries of 3 papers on machine learning applications in wireless communication technology. The paper deals with the need for integration of machine learning in wireless communication, types of machine learning techniques used in wireless communication, advantages and potential of ML in wireless communication, and implementation parameters of ML in wireless communication, as well as a study on RSS-Based Classification of usage in indoor millimeter-wave wireless networks.