Deep Reinforcement Learning for Wireless Communications and Networking: Theory, Applications and Implementation 9781119873679

Deep Reinforcement Learning for Wireless Communications and Networking Comprehensive guide to Deep Reinforcement Learni

469 118 13MB

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Table of contents :
Cover
Table of Contents
Title Page
Copyright
Dedication
Notes on Contributors
Foreword
Preface
Acknowledgments
Acronyms
Introduction
Part I: Fundamentals of Deep Reinforcement Learning
1 Deep Reinforcement Learning and Its Applications
1.1 Wireless Networks and Emerging Challenges
1.2 Machine Learning Techniques and Development of DRL
1.3 Potentials and Applications of DRL
1.4 Structure of this Book and Target Readership
1.5 Chapter Summary
References
2 Markov Decision Process and Reinforcement Learning
2.1 Markov Decision Process
2.2 Partially Observable Markov Decision Process
2.3 Policy and Value Functions
2.4 Bellman Equations
2.5 Solutions of MDP Problems
2.6 Reinforcement Learning
2.7 Chapter Summary
References
3 Deep Reinforcement Learning Models and Techniques
3.1 Value-Based DRL Methods
3.2 Policy-Gradient Methods
3.3 Deterministic Policy Gradient (DPG)
3.4 Natural Gradients
3.5 Model-Based RL
3.6 Chapter Summary
References
4 A Case Study and Detailed Implementation
4.1 System Model and Problem Formulation
4.2 Implementation and Environment Settings
4.3 Simulation Results and Performance Analysis
4.4 Chapter Summary
References
Note
Part II: Applications of DRL in Wireless Communications and Networking
5 DRL at the Physical Layer
5.1 Beamforming, Signal Detection, and Decoding
5.2 Power and Rate Control
5.3 Physical-Layer Security
5.4 Chapter Summary
References
6 DRL at the MAC Layer
6.1 Resource Management and Optimization
6.2 Channel Access Control
6.3 Heterogeneous MAC Protocols
6.4 Chapter Summary
References
7 DRL at the Network Layer
7.1 Traffic Routing
7.2 Network Slicing
7.3 Network Intrusion Detection
7.4 Chapter Summary
References
8 DRL at the Application and Service Layer
8.1 Content Caching
8.2 Data and Computation Offloading
8.3 Data Processing and Analytics
8.4 Chapter Summary
References
Part III: Challenges, Approaches, Open Issues, and Emerging Research Topics
9 DRL Challenges in Wireless Networks
9.1 Adversarial Attacks on DRL
9.2 Multiagent DRL in Dynamic Environments
9.3 Other Challenges
9.4 Chapter Summary
References
10 DRL and Emerging Topics in Wireless Networks
10.1 DRL for Emerging Problems in Future Wireless Networks
10.2 Advanced DRL Models
10.3 Chapter Summary
References
Note
Index
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