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1.ZJU-UIUC Institute, Interdisciplinary Center for Quantum Information, State Key Laboratory of Extreme Photonics and Instrumentation, Zhejiang University, Hangzhou, China
2.ZJU-Hangzhou Global Science and Technology Innovation Center, Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang, Zhejiang University, Hangzhou, China
3.Jinhua Institute of Zhejiang University, Zhejiang University, Jinhua, China
4.Shanghai Key Laboratory of Navigation and Location-Based Services, Shanghai Jiao Tong University, Shanghai, China
Chao Qian (chaoq@intl.zju.edu.cn)
Hongsheng Chen (hansomchen@zju.edu.cn)
Received:26 August 2024,
Revised:07 December 2024,
Accepted:2024-12-19,
Published Online:25 February 2025,
Published:30 April 2025
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Qian, C., Tian, L. W. & Chen, H. S. Progress on intelligent metasurfaces for signal relay, transmitter, and processor. Light: Science & Applications, 14, 886-901 (2025).
Qian, C., Tian, L. W. & Chen, H. S. Progress on intelligent metasurfaces for signal relay, transmitter, and processor. Light: Science & Applications, 14, 886-901 (2025). DOI: 10.1038/s41377-024-01729-2.
Pursuing higher data rate with limited spectral resources is a longstanding topic that has triggered the fast growth of modern wireless communication techniques. However
the massive deployment of active nodes to compensate for propagation loss necessitates high hardware expenditure
energy consumption
and maintenance cost
as well as complicated network interference issues. Intelligent metasurfaces
composed of a number of subwavelength passive or active meta-atoms
have recently found to be a new paradigm to actively reshape wireless communication environment in a green way
distinct from conventional works that passively adapt to the surrounding. In this review
we offer a unified perspective on how intelligent metasurfaces can facilitate wireless communication in three manners: signal relay
signal transmitter
and signal processor. We start by the basic modeling of wireless channel and the evolution of metasurfaces from passive
active to intelligent metasurfaces. Integrated with various deep learning algorithms
intelligent metasurfaces adapt to cater for the ever-changing environments without human intervention. Then
we overview specific experimental advancements using intelligent metasurfaces. We conclude by identifying key issues in the practical implementations of intelligent metasurfaces
and surveying new directions
such as gain metasurfaces and knowledge migration.
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