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Integrated sensing and communication based on space-time-coding metasurfaces

Author

Listed:
  • Xiao Qing Chen

    (Southeast University)

  • Lei Zhang

    (Southeast University)

  • Yi Ning Zheng

    (Southeast University)

  • Shuo Liu

    (Southeast University)

  • Zhuo Ran Huang

    (Southeast University)

  • Jing Cheng Liang

    (Southeast University)

  • Marco Renzo

    (Université Paris-Saclay, CNRS, CentraleSupélec
    King’s College London, Centre for Telecommunications Research)

  • Vincenzo Galdi

    (University of Sannio)

  • Tie Jun Cui

    (Southeast University)

Abstract

Programmable metasurfaces (PMs), also called reconfigurable intelligent surfaces (RISs), are planar structures capable of dynamically manipulating electromagnetic waves in real-time. Regarded as a key enabling technology for implementing smart wireless propagation environments, PMs/RISs also serve as an ideal supporting platform for integrated sensing and communication (ISAC). Here, we propose two ISAC schemes based on a special type of PMs/RISs: space-time-coding metasurfaces (STCMs). By leveraging space-time-coding strategies, STCMs simultaneously control the propagation at the fundamental (carrier) frequency for reliable wireless communication and generate spatially distributed harmonics for sensing. The proposed schemes seamlessly integrate both communication and sensing on a shared hardware platform, eliminating the need for additional sensors. For experimental validation, we implemented an ISAC system using a 2-bit STCM operating at microwave frequencies. Experimental results align with theoretical predictions, confirming the practical viability and effectiveness of the proposed ISAC schemes for applications in communication, imaging, radar, and sensing systems.

Suggested Citation

  • Xiao Qing Chen & Lei Zhang & Yi Ning Zheng & Shuo Liu & Zhuo Ran Huang & Jing Cheng Liang & Marco Renzo & Vincenzo Galdi & Tie Jun Cui, 2025. "Integrated sensing and communication based on space-time-coding metasurfaces," Nature Communications, Nature, vol. 16(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-57137-6
    DOI: 10.1038/s41467-025-57137-6
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    References listed on IDEAS

    as
    1. Lianlin Li & Hengxin Ruan & Che Liu & Ying Li & Ya Shuang & Andrea Alù & Cheng-Wei Qiu & Tie Jun Cui, 2019. "Machine-learning reprogrammable metasurface imager," Nature Communications, Nature, vol. 10(1), pages 1-8, December.
    2. Lianlin Li & Tie Jun Cui & Wei Ji & Shuo Liu & Jun Ding & Xiang Wan & Yun Bo Li & Menghua Jiang & Cheng-Wei Qiu & Shuang Zhang, 2017. "Electromagnetic reprogrammable coding-metasurface holograms," Nature Communications, Nature, vol. 8(1), pages 1-7, December.
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