Chongfan Technology
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18
2025
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03
Light | Overview: Wireless signal relaying, transmission, and processing based on intelligent metasurfaces
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Introduction
Metasurfaces precisely manipulate key physical quantities of electromagnetic waves, such as amplitude, phase, and angular momentum, through ingenious design of unit structures and spatial arrangements. Their ultra-thin, lightweight, and low-loss characteristics are driving the transformation of electromagnetic space integration and integrated optoelectronic devices. Intelligent metasurfaces, based on tunable metasurfaces and driven by artificial intelligence algorithms, rapidly calculate the coding state of the metasurface according to user-defined input and actual scene requirements, achieving far-field customization, frequency selection, and topological state switching. They show great potential in electromagnetic stealth, radar detection, remote sensing imaging, and wireless communication.
Recently,Zhejiang UniversityResearcher Qian Chao - Professor Chen Hongsheng's teampublished"Progress on intelligent metasurfaces for signal relay， transmitter， and processor"inLight: Science & Applicationsa review article. Researcher Qian Chaois the first and co-corresponding author of the paper,Professor Chen Hongshengis the co-corresponding author.The paper discusses the inverse design algorithms and experimental progress of intelligent metasurfaces, comprehensively summarizing their applications in wireless signal relaying, transmission, and processing.
Figure 1: Three typical applications of intelligent metasurfaces: relaying, transmission, and processing
"Sense-Decide-Respond" Intelligent Metasurface
Over the past decade, metasurfaces have undergone three key development stages: passive metasurfaces, active/tunable metasurfaces, and intelligent metasurfaces. The significant characteristics of intelligent metasurfaces includeon-demand customization, rapid adaptation, and no manual operation. They possess sense-decide-respond capabilities: sensing is achieved by detecting devices extracting the characteristics of incident electromagnetic waves and the metasurface's own state; decision-making utilizes intelligent algorithms to calculate the metasurface distribution that meets current needs; and response uses the tunable metasurface to actually reconstruct the electromagnetic scattering field distribution. Tunable metasurfaces are realized by loading tunable materials or active components in subwavelength units, including mechanical control based on microelectromechanical systems, electrical control based on varactor diodes and conductive oxides, optical control based on phase-change materials, and nonlinear optical control.
Figure 2: The development history of metasurfaces
Deep learning is the core driving force behind intelligent metasurfaces, exploring the complex nonlinear interaction between electromagnetic waves and metasurfaces, establishing a "high-speed channel" between electromagnetic scattering and metasurfaces, and driving the adaptive control of electromagnetic scattering by intelligent metasurfaces. The paper focuses on new algorithms in inverse design, addressing challenges such as non-unique solutions, low data and network utilization, semi-known input scenarios, and cross-scenario knowledge transfer.
Figure 3. New driving algorithms for intelligent metasurfaces
Wireless Signal Relaying, Transmission, and Processing Based on Intelligent Metasurfaces
Intelligent metasurfaces provide a green and efficient means of channel reshaping for wireless communication. Compared to the traditional approach of deploying a large number of complex and energy-consuming base stations, they can significantly reduce hardware expenditure and maintenance costs. The paper uses cascaded channel models and sparse angular channel models for channel modeling of intelligent metasurfaces. The intelligent metasurface's control of wireless signals is not limited to relaying and filling blind spots; it can also act as a simple transmitter and, more interestingly, directly process signals in electromagnetic space.
Signal Relaying.Intelligent metasurfaces adjust the state of each unit to directionally reflect beams to areas with weaker signal strength, establishing non-line-of-sight links on demand, supporting edge users, and thus improving network coverage depth and quality and reducing blind spots.
Signal Transmission.Compared to traditional methods requiring complex RF chains such as mixers and antennas, intelligent metasurfaces can control electromagnetic waves in both time and space dimensions, creating simple signal transmitters and enabling space-time multiplexing communication and index modulation.
Signal Processing.Using algorithms such as topological optimization and deep learning, the spatial structure of the intelligent metasurface is optimized to perform signal analysis and processing directly in electromagnetic space, such as detection, encoding, and dimensionality reduction, with advantages of high processing speed and low power consumption.
Summary and Outlook
Algorithm modeling and experimental research related to intelligent metasurfaces have also made significant progress. However, further improving the performance of intelligent metasurfaces is limited by the physical characteristics of tunable metasurfaces, such as gain and bandwidth. There are still many scientific and engineering problems to be explored in the algorithm modeling and experimental applications of large-size distributed intelligent metasurfaces.
Paper Information
Qian, C., Tian, L. & Chen, H. Progress on intelligent metasurfaces for signal relaying, transmitter, and processor. Light Sci Appl 14, 93 (2025).
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