<p class="MsoBodyText" style="text-align: justify;"><span style="font-size: 11.0pt; font-family: 'Calibri',sans-serif; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; color: black;">The authors present research results on <a name="_Hlk201659877"></a>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.</span><span style="font-size: 11.0pt; font-family: 'Calibri',sans-serif; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; color: black; mso-fareast-language: ZH-CN;"> </span></p><p class="MsoBodyText" style="text-align: justify;"><span style="font-size: 11.0pt; font-family: 'Calibri',sans-serif; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; color: black;">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.</span></p><p class="MsoBodyText" style="text-align: justify;"><span style="font-size: 11.0pt; font-family: 'Calibri',sans-serif; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin; mso-bidi-theme-font: minor-latin;">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.</span></p>

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AI for Wireless Physical Layer

  • Long Zhao,
  • Hongrui Shen,
  • Kan Zheng

摘要

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.