AI for Wireless Physical Layer
The authors present research results on AI for wireless physical layer. Both the typical applications and model design for intelligent physical-layer communication are addressed. Along with a review of the literatures, the authors first present the integration of artificial intelligence (AI) and communication for sixth generation (6G) network or future communication networks. The authors also introduce the typic applications of AI on physical-layer technology, i.e., channel estimation and interpolation, the intelligent CSI feedback and precoding technologies for FDD and TDD systems, respectively, beam management for cell coverage.

Finally, this SpringerBrief discusses future research directions. The authors believe the example mechanisms and demonstration of AI-based physical-layer communication and related findings could reveal useful insights for the application of AI on wireless network and spur. It’s a new line of thinking for the performance improvement of future communication networks.

This SpringerBrief targets advanced-level students majoring in the areas of communication engineering, information engineering, intelligent science, computer science, engineering and electrical engineering professionals and researchers seeking AI-based solutions for 6G physical-layer communications will also find this book a useful resource.

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AI for Wireless Physical Layer
The authors present research results on AI for wireless physical layer. Both the typical applications and model design for intelligent physical-layer communication are addressed. Along with a review of the literatures, the authors first present the integration of artificial intelligence (AI) and communication for sixth generation (6G) network or future communication networks. The authors also introduce the typic applications of AI on physical-layer technology, i.e., channel estimation and interpolation, the intelligent CSI feedback and precoding technologies for FDD and TDD systems, respectively, beam management for cell coverage.

Finally, this SpringerBrief discusses future research directions. The authors believe the example mechanisms and demonstration of AI-based physical-layer communication and related findings could reveal useful insights for the application of AI on wireless network and spur. It’s a new line of thinking for the performance improvement of future communication networks.

This SpringerBrief targets advanced-level students majoring in the areas of communication engineering, information engineering, intelligent science, computer science, engineering and electrical engineering professionals and researchers seeking AI-based solutions for 6G physical-layer communications will also find this book a useful resource.

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AI for Wireless Physical Layer

AI for Wireless Physical Layer

AI for Wireless Physical Layer
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AI for Wireless Physical Layer

AI for Wireless Physical Layer

Overview

The authors present research results on AI for wireless physical layer. Both the typical applications and model design for intelligent physical-layer communication are addressed. Along with a review of the literatures, the authors first present the integration of artificial intelligence (AI) and communication for sixth generation (6G) network or future communication networks. The authors also introduce the typic applications of AI on physical-layer technology, i.e., channel estimation and interpolation, the intelligent CSI feedback and precoding technologies for FDD and TDD systems, respectively, beam management for cell coverage.

Finally, this SpringerBrief discusses future research directions. The authors believe the example mechanisms and demonstration of AI-based physical-layer communication and related findings could reveal useful insights for the application of AI on wireless network and spur. It’s a new line of thinking for the performance improvement of future communication networks.

This SpringerBrief targets advanced-level students majoring in the areas of communication engineering, information engineering, intelligent science, computer science, engineering and electrical engineering professionals and researchers seeking AI-based solutions for 6G physical-layer communications will also find this book a useful resource.

Product Details

ISBN-13: 9783032013668
Publisher: Springer Nature Switzerland
Publication date: 09/01/2025
Series: SpringerBriefs in Computer Science
Pages: 88
Product dimensions: 6.10(w) x 9.25(h) x (d)

About the Author

Long Zhao is currently an Associate Professor of Beijing University of Posts and Telecommunications (BUPT). He got his Ph. D degree from BUPT, China, in 2015. He was a research scholar in Engineering School of Columbia University, US from Apr. 2014 to Mar. 2015. He joined BUPT in 2015 as lecturer. His research interests are Smart Communications and Massive Signal Processing.

Hongrui Shen is currently a Ph.D. candidate in Beijing University of Posts and Telecommunications (BUPT), China. He received his B.S degree in 2021 from Beijing University of Posts and Telecommunications (BUPT). His research interests include wireless communications and deep learning.

Kan Zheng is currently a Full Professor with Ningbo University, Ningbo, China. He received the B.S., M.S., and Ph.D. degrees from the Beijing University of Posts and Telecommunications, China, in 1996, 2000, and 2005, respectively. He has rich experience in research and standardization of new emerging technologies. He holds editorial board positions with several journals and also served in the organizing/TPC committees for conferences.

Table of Contents

Chapter 1. Introduction.- Chapter 2. Intelligent Channel Estimation Technology.- Chapter 3. Intelligent CSI Feedback Technology for FDD Systems.- Chapter 4. Intelligent Precoding Technology for TDD Systems.- Chapter 5. Intelligent Beam Management Technology.- Chapter 6. Conclusion and Outlook.

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