4.7 Article

Toward Ubiquitous Sensing and Localization With Reconfigurable Intelligent Surfaces

Journal

PROCEEDINGS OF THE IEEE
Volume 110, Issue 9, Pages 1401-1422

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JPROC.2022.3169771

Keywords

Sensors; Location awareness; Robot sensing systems; Wireless sensor networks; Radio frequency; OFDM; Wireless networks; Implementation; localization; reconfigurable intelligent surfaces (RISs); wireless sensing

Funding

  1. National Key Research and Development Project of China [2020YFB1807100]
  2. National Natural Science Foundation of China [61829101, 61941101, 62032003]
  3. Beijing Natural Science Foundation [4222005, L212027]
  4. State Key Laboratory of Advanced Optical Communication Systems Networks, China
  5. U.S. National Science Foundation [CNS-2107216, EARS-1839818]

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This tutorial discusses the future development trend of wireless sensing and localization in cellular systems, and introduces the method and challenges of using reconfigurable intelligent surfaces (RIS) to improve wireless sensing and localization performance.
In future cellular systems, wireless localization and sensing functions will be built-in for specific applications, e.g., navigation, transportation, and healthcare, and to support flexible and seamless connectivity. Driven by this trend, the need for fine-resolution sensing solutions and centimeter-level localization accuracy arises, while the accuracy of current wireless systems is limited by the quality of the propagation environment. Recently, with the development of new materials, reconfigurable intelligent surfaces (RISs) provide an opportunity to reshape and control the electromagnetic characteristics of the environment, which can be utilized to improve the performance of wireless sensing and localization. In this tutorial, we will first review the background and motivation for utilizing wireless signals for sensing and localization. Next, we will introduce how to incorporate RIS into applications of sensing and localization, including key challenges and enabling techniques, and then, some case studies will be presented. Finally, future research directions will also be discussed.

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