
Machine Learning for Radio Resource Management and Optimization in 5G and Beyond
- 272 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
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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Information
Table of contents
- Cover
- Half Title
- Title Page
- Copyright Page
- Table of Contents
- Preface
- Editor biographies
- List of contributors
- Chapter 1 ◾ Fundamentals of 5G and beyond networks
- Chapter 2 ◾ Optimizing resource allocation in intelligent communication networks: Fundamentals and challenges
- Chapter 3 ◾ Radio resource management for M2M communications in cellular networks
- Chapter 4 ◾ Integrating blockchain for secure and efficient radio resource management in 5G and beyond networks
- Chapter 5 ◾ Federated learning for intelligent network management in 5G
- Chapter 6 ◾ Non-orthogonal multiple access wireless systems using deep learning
- Chapter 7 ◾ Advancements in machine learning techniques for optimization of massive MIMO design
- Chapter 8 ◾ Predictive modeling of household power consumption using machine learning and meta-heuristic optimization technique
- Chapter 9 ◾ Intelligent reinforcement learning-based scheduling in 5G networks and beyond
- Chapter 10 ◾ AR/VR-based object detection for blind people using 5G communication
- Chapter 11 ◾ Exploring sentiment patterns in social media networks: The impact of AI, deep learning, and large models in the 5G landscape
- Chapter 12 ◾ 5G and AI-based data fusion in intelligent networks
- Index