Enhancing Near-Field Wireless Localization With LiDAR-Assisted RIS in Multipath Environments

Abstract

In next-generation wireless networks that adopt millimeter-waves and large reconfigurable intelligent surfaces (RISs), the user is expected to be in the near-field region, where the widely adopted far-field algorithms based on far-field can yield low positioning accuracy. Also, the localization of user equipment (UE) becomes more challenging in multipath environments. In this letter, we propose a localization algorithm for a UE in the near-field of a RIS in multipath environments. The proposed scheme utilizes a light detection and ranging (LiDAR) to assist the UE positioning by providing geometric information about some of the scatterers in the environment. This information is fed to a sparse recovery algorithm to improve the localization accuracy of the UE by reducing the number of variables (i.e., angle of arrivals and distances) to be estimated. The numerical results show that the proposed scheme can improve the localization accuracy by 65% compared to the standard compressed sensing (CS) scheme.