Deep Learning in Wireless Communications

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Description

The book offers a focused examination of deep learning-based wireless communication systems and their applications. While both principles and engineering practice are explored, greater emphasis is placed on the latter. The book offers an in-depth exploration of major topics such as cognitive spectrum intelligence, learning resource allocation optimization, transmission intelligence, learning traffic and mobility prediction, and security in wireless communication. Notably, the book provides a comprehensive and systematic treatment of practical issues related to intelligent wireless communication, making it particularly useful for those seeking to learn about practical solutions in AI-based wireless resource management. This book is a valuable resource for researchers, engineers, and graduate students in the fields of wireless communication, telecommunications, and related areas.


Table of contents (8 chapters)
Front Matter
Pages i-xiii
Introduction to Intelligence Wireless Communication
Haijun Zhang, Ning Yang
Pages 1-11
Cognitive Spectrum Intelligence
Haijun Zhang, Ning Yang
Pages 13-31
Learning Resource Allocation Optimization
Haijun Zhang, Ning Yang
Pages 33-66
Transmission Intelligence
Haijun Zhang, Ning Yang
Pages 67-88
Learning Traffic and Mobility Prediction
Haijun Zhang, Ning Yang
Pages 89-107
Software Defined Networking
Haijun Zhang, Ning Yang
Pages 109-119
Security in Wireless Communication
Haijun Zhang, Ning Yang
Pages 121-131
6G Driving Applications with Deep Learning
Haijun Zhang, Ning Yang
Pages 133-142

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