English

Assessing the Potential of Space-Time-Coding Metasurfaces for Sensing and Localization

Signal Processing 2024-01-09 v1 Networking and Internet Architecture Applications

Abstract

Intelligent metasurfaces are one of the favorite technologies for integrating sixth-generation (6G) networks, especially the reconfigurable intelligent surface (RIS) that has been extensively researched in various applications. In this context, a feature that deserves further exploration is the frequency scattering that occurs when the elements are periodically switched, referred to as Space-Time-Coding metasurface (STCM) topology. This type of topology causes impairments to the established communication methods by generating undesirable interference both in frequency and space, which is worsened when using wideband signals. Nevertheless, it has the potential to bring forward useful features for sensing and localization. This work exploits STCM sensing capabilities in target detection, localization, and classification using narrowband downlink pilot signals at the base station (BS). The results of this novel approach reveal the ability to retrieve a scattering point (SP) localization within the sub-centimeter and sub-decimeter accuracy depending on the SP position in space. We also analyze the associated detection and classification probabilities, which show reliable detection performance in the whole analyzed environment. In contrast, the classification is bounded by physical constraints, and we conclude that this method presents a promising approach for future integrated sensing and communications (ISAC) protocols by providing a tool to perform sensing and localization services using legacy communication signals.

Keywords

Cite

@article{arxiv.2401.03189,
  title  = {Assessing the Potential of Space-Time-Coding Metasurfaces for Sensing and Localization},
  author = {Herman L. dos Santos and Martin Voigt Vejling and Taufik Abrão and Petar Popovski},
  journal= {arXiv preprint arXiv:2401.03189},
  year   = {2024}
}

Comments

13 pages, 9 figures, 1 table. Manuscript submitted to IEEE-TWC on January 6th, 2024

R2 v1 2026-06-28T14:10:07.295Z