Fundamentals of Machine Learning in Communication Systems
Shivani Sharma, Avani Vyas · 2025
This chapter addresses the escalating network density and the unprecedented surge in network traffic attributed to the substantial proliferation of connected devices and online services. The imperative for intelligent network operations to meet the demands of evolving communication devices and services has led to the application of machine learning (ML) across diverse network types and technologies. This chapter offers a comprehensive overview of current research endeavors focusing on ML applications within communication networks. The discussion encompasses the three layers of communication networks—physical, access, and network layers—and explores emerging computing and networking paradigms such as multi-access edge computing (MEC), software-defined networking (SDN), network functions virtualization (NFV), along with a succinct examination of ML-based network security. Additionally, the work identifies key research challenges for the future, providing insights to catalyze further exploration in crucial areas within this domain.