A Survey on Machine Learning-based Medium access control technology for 6G requirements

Abstract

In this paper, we present research trends about machine learning-based medium access control technology for 6G requirements. The complex network environment of 6G requires more intelligent communication than the 5G environment. Particularly in the medium access control layer, plenty of studies are being conducted on resource allocation and random-access problems that have become difficult to solve with existing approaches due to the increased complexity of the network. This paper briefly introduces about 6G requirements and machine learning, then investigates the latest studies on resource allocation and random-access, which consider 6G requirements using machine learning techniques. Moreover, future research directions for machine learning-based medium access control technologies are also presented.