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

472 119 13MB

English Pages 288 Year 2023

Report DMCA / Copyright

DOWNLOAD EPUB FILE

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
End User License Agreement

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

  • 0 0 0
  • Like this paper and download? You can publish your own PDF file online for free in a few minutes! Sign Up
Recommend Papers
Reinforcement Learning for Maritime Communications (Wireless Networks) 3031321375, 9783031321375
Reinforcement Learning for Maritime Communications (Wireless Networks) 3031321375, 9783031321375

This book demonstrates that the reliable and secure communication performance of maritime communications can be signific

103 45 7MB Read more

Deep Reinforcement Learning: Fundamentals, Research and Applications 9811540950, 9789811540950
Deep Reinforcement Learning: Fundamentals, Research and Applications 9811540950, 9789811540950

Deep reinforcement learning (DRL) is the combination of reinforcement learning (RL) and deep learning. It has been able

1,072 160 44MB Read more

Deep reinforcement learning 9789811382840, 9789811382857
Deep reinforcement learning 9789811382840, 9789811382857

503 87 11MB Read more

DEEP REINFORCEMENT LEARNING (Yuxi Li)
DEEP REINFORCEMENT LEARNING (Yuxi Li)

713 49 2MB Read more

Deep Reinforcement Learning for Wireless Networks [1st ed. 2019] 9783030105464, 9783030105457, 3030105466
Deep Reinforcement Learning for Wireless Networks [1st ed. 2019] 9783030105464, 9783030105457, 3030105466

106 15 8MB Read more

Artificial Intelligence: Reinforcement Learning in Python: Complete guide to artificial intelligence and machine learning, prep for deep reinforcement learning
Artificial Intelligence: Reinforcement Learning in Python: Complete guide to artificial intelligence and machine learning, prep for deep reinforcement learning

When people talk about artificial intelligence, they usually don’t mean supervised and unsupervised machine learning. T

99 88 262KB Read more

Deep Reinforcement Learning in Action 9781617295430, 1617295434
Deep Reinforcement Learning in Action 9781617295430, 1617295434

Summary Humans learn best from feedback—we are encouraged to take actions that lead to positive results while deterred b

165 75 9MB Read more

Deep Reinforcement Learning 9789811906381, 9789811906374, 9811906386
Deep Reinforcement Learning 9789811906381, 9789811906374, 9811906386

Deep reinforcement learning has attracted considerable attention recently. Impressive results have been achieved in such

110 102 52MB Read more

Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems [1 ed.] 0367620065, 9780367620066
Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems [1 ed.] 0367620065, 9780367620066

This book offers the latest advances and results in the fields of Machine Learning and Deep Learning for Wireless Commun

245 47 18MB Read more

Foundations of Deep Reinforcement Learning: Theory and Practice in Python 0135172381, 9780135172384
Foundations of Deep Reinforcement Learning: Theory and Practice in Python 0135172381, 9780135172384

The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice Deep reinforcement lear

486 119 7MB Read more

Our partners will collect data and use cookies for ad personalization and measurement. Learn how we and our ad partner Google, collect and use data. Agree Cookies