Machine Learning for Radio Resource Management and Optimization in 5G and Beyond

Mariyam Ouaissa, Mariya Ouaissa, Hanane Lamaazi, Khadija Slimani, Ihtiram Raza Khan, B. Sundaravadivazhagan

Research output: Book/ReportBook

Abstract

Machine Learning for Radio Resource Management and Optimization in 5G and Beyond highlights a new line of research that uses innovative technologies and methods based on artificial intelligence/machine learning techniques to address issues and challenges related to radio resource management in 5G and 6G communication systems. This book provides comprehensive coverage of current and emerging waveform design, channel modeling, multiple access, random access, scheduling, network slicing, and resource optimization for 5G wireless networks and beyond. This book is suitable for researchers, scholars, and industry professionals working in different fields related to mobile networks and intelligent systems. Additionally, it serves as a hands-on resource for students interested in the fields of cellular networks (5G/6G) and computational intelligence.

Original languageEnglish
PublisherCRC Press
Number of pages234
ISBN (Electronic)9781040327616
ISBN (Print)9781032844732
DOIs
Publication statusPublished - Jan 1 2025

ASJC Scopus subject areas

  • General Computer Science
  • General Engineering
  • General Energy

Fingerprint

Dive into the research topics of 'Machine Learning for Radio Resource Management and Optimization in 5G and Beyond'. Together they form a unique fingerprint.

Cite this