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

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

  1. 272 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

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

About this book

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.

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Yes, you can access Machine Learning for Radio Resource Management and Optimization in 5G and Beyond by Mariyam Ouaissa,Mariya Ouaissa,Hanane Lamaazi,Khadija Slimani,Ihtiram Raza Khan,B. Sundaravadivazhagan in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Table of Contents
  6. Preface
  7. Editor biographies
  8. List of contributors
  9. Chapter 1 ◾ Fundamentals of 5G and beyond networks
  10. Chapter 2 ◾ Optimizing resource allocation in intelligent communication networks: Fundamentals and challenges
  11. Chapter 3 ◾ Radio resource management for M2M communications in cellular networks
  12. Chapter 4 ◾ Integrating blockchain for secure and efficient radio resource management in 5G and beyond networks
  13. Chapter 5 ◾ Federated learning for intelligent network management in 5G
  14. Chapter 6 ◾ Non-orthogonal multiple access wireless systems using deep learning
  15. Chapter 7 ◾ Advancements in machine learning techniques for optimization of massive MIMO design
  16. Chapter 8 ◾ Predictive modeling of household power consumption using machine learning and meta-heuristic optimization technique
  17. Chapter 9 ◾ Intelligent reinforcement learning-based scheduling in 5G networks and beyond
  18. Chapter 10 ◾ AR/VR-based object detection for blind people using 5G communication
  19. Chapter 11 ◾ Exploring sentiment patterns in social media networks: The impact of AI, deep learning, and large models in the 5G landscape
  20. Chapter 12 ◾ 5G and AI-based data fusion in intelligent networks
  21. Index