Generative Learning for Wireless Communications: Fundamentals and Applications

ISBN 10: 0443414971 / ISBN 13: 9780443414978

Published by Academic Press, 2026

About this Item

2026. paperback. . . . . . Books ship from the US and Ireland.

Seller Inventory # V9780443414978

Bibliographic Details

• Title: Generative Learning for Wireless Communications: Fundamentals and Applications
• Publisher: Academic Press
• Publication Date: 2026
• Language: English
• ISBN 10: 0443414971
• ISBN 13: 9780443414978
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Generative learning (GL) has emerged as an essential tool for data processing and network optimization in the broad area of next-generation communication systems. Generative Learning for Wireless Communications: Fundamentals and Applications provides a comprehensive and systematic tutorial for applying generative learning models to wireless communications. It explains the core concepts of state-of-the-art generative learning models, including generative adversarial nets, variational autoencoder, and other advanced models, such as transformers and diffusion models, and then shows their application to specific areas in wireless communications.

• Explains the fundamental concepts of the state-of-the-art generative learning models
• Presents the most advanced methods of generative AI in wireless communications
• Gives practical guidance on how to apply generative AI in wireless communications
• Includes case studies and algorithm designs
• Presents the critical challenges of GL today and promising future directions

About the Authors

Dr. Songyang Zhang received the Ph.D. degree from the Department of Electrical and Computer Engineering at the University of California, Davis, CA, USA. He is currently an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Louisiana at Lafayette, Lafayette, LA, USA.

Dr. Shuai Zhang received his Ph.D. degree from the Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute (RPI) in 2021. He is currently an Assistant Professor in the Ying Wu College of Computing at the New Jersey Institute of Technology (NJIT), NJ, USA.

Prof. Chuan Huang received his Ph.D. degree from the Department of Electrical and Computer Engineering at Texas A&M University, College Station, TX, USA, in 2012. He is currently a Professor in Shenzhen Institute for Advanced Study at University of Electronic Science and Technology of China, Shenzhen, China.