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AI for wireless physical layer

Record Type:	Electronic resources : Monograph/item
Title/Author:	AI for wireless physical layer/ by Long Zhao, Hongrui Shen, Kan Zheng.
Author:	Zhao, Long.
other author:	Shen, Hongrui.
Published:	Cham :Springer Nature Switzerland : : 2025.,
Description:	xv, 88 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Wireless communication systems. -
Online resource:	https://doi.org/10.1007/978-3-032-01367-5
ISBN:	9783032013675

AI for wireless physical layer
Zhao, Long.

AI for wireless physical layer[electronic resource] /by Long Zhao, Hongrui Shen, Kan Zheng. - Cham :Springer Nature Switzerland :2025. - xv, 88 p. :ill. (some col.), digital ;24 cm. - SpringerBriefs in computer science,2191-5776. - SpringerBriefs in computer science..

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.

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.

ISBN: 9783032013675

Standard No.: 10.1007/978-3-032-01367-5doiSubjects--Topical Terms:

567106
Wireless communication systems.

LC Class. No.: TK5103.2

Dewey Class. No.: 621.382

AI for wireless physical layer
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245 1 0 $a AI for wireless physical layer $h [electronic resource] / $c by Long Zhao, Hongrui Shen, Kan Zheng.
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2025.
300 $a xv, 88 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a SpringerBriefs in computer science, $x 2191-5776
505 0 $a 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.
520 $a 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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650 0 $a Artificial intelligence. $3 516317
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650 2 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Wireless and Mobile Communication. $3 3338159
700 1 $a Shen, Hongrui. $3 3791152
700 1 $a Zheng, Kan. $3 2186748
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