Optimizing 5G Networks with Machine Learning: Enhancing Spectrum and Energy Efficiency

Abstract

The advent of 5G technology has ushered in a new era of connectivity, characterized by increased data rates, ultra-reliable low-latency communication, and massive machine-type communication. However, the challenges associated with spectrum efficiency and energy efficiency have become increasingly prominent as network demands grow. This research paper explores the role of machine learning (ML) in addressing these challenges, particularly in the context of 5G networks. By examining the applications of ML in cognitive radios, massive MIMO systems, virtualization, resource optimization, and spectrum sharing, this study highlights the transformative potential of ML in optimizing 5G networks.