AI for Wireless Physical Layer
暫譯: 無線物理層的人工智慧

Zhao, Long, Shen, Hongrui, Zheng, Kan

AI for Wireless Physical Layer
  • 出版商: Springer
  • 出版日期: 2025-09-01
  • 售價: $2,350
  • 貴賓價: 9.5 折 $2,233
  • 語言: 英文
  • 頁數: 88
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3032013666
  • ISBN-13: 9783032013668
  • 相關分類: 無人機、Wireless-networks

    • 海外代購書籍(需單獨結帳)

相關主題

商品描述

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.

商品描述(中文翻譯)

作者提出了關於無線物理層的人工智慧（AI）研究結果。文中探討了智能物理層通信的典型應用和模型設計。隨著文獻的回顧，作者首先介紹了人工智慧（AI）與第六代（6G）網絡或未來通信網絡的整合。作者還介紹了AI在物理層技術上的典型應用，即通道估計和插值、針對FDD和TDD系統的智能CSI反饋和預編碼技術，以及用於小區覆蓋的波束管理。

最後，這本SpringerBrief討論了未來的研究方向。作者認為，基於AI的物理層通信的示例機制和演示及相關發現，能夠為AI在無線網絡上的應用提供有用的見解並激發靈感。這是一種針對未來通信網絡性能改進的新思維。

這本SpringerBrief的目標讀者是專攻通信工程、資訊工程、智能科學、計算機科學的高級學生，以及尋求基於AI的6G物理層通信解決方案的工程和電機工程專業人士和研究人員，這本書對他們來說也是一個有用的資源。

作者簡介

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.

作者簡介(中文翻譯)

趙龍目前是北京郵電大學（BUPT）的副教授。他於2015年在北京郵電大學獲得博士學位。2014年4月至2015年3月，他曾在美國哥倫比亞大學工程學院擔任研究學者。他於2015年加入北京郵電大學擔任講師。他的研究興趣包括智慧通信和大規模信號處理。 沈洪瑞目前是北京郵電大學（BUPT）的博士候選人。他於2021年獲得北京郵電大學的學士學位。他的研究興趣包括無線通信和深度學習。 鄭侃目前是中國寧波大學的正教授。他於1996年、2000年和2005年分別在北京郵電大學獲得學士、碩士和博士學位。他在新興技術的研究和標準化方面擁有豐富的經驗。他擔任多本期刊的編輯委員會成員，並在會議的組織/技術程序委員會中任職。

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