RIS-Aided Near-Field Localization and Channel Estimation for the Terahertz System

Abstract

The affordable hardware cost of ultra-large (XL) reconfigurable intelligent surfaces (RIS) renders them attractive solutions for the performance enhancement of localization and communication systems. However, XL-RIS results in near-field propagation channels, especially for the high-frequency terahertz (THz) communication system, which poses significant challenges for localization and channel estimation. In this paper, we focus on the spherical wavefront propagation in the near field of the THz system with the assistance of a RIS. A near-field channel estimation and localization (NF-JCEL) algorithm is proposed based on the derived second-order Fresnel approximation of the near-field channel model. To be specific, we carefully devise a down-sampled Toeplitz covariance matrix, which enables the decoupling and separate estimation of user equipment (UE) distances and angles of arrival (AoAs). Using the sub-space based method and one-dimensional search, we estimate the angles of arrival (AoAs) and user equipment (UE) distances. The channel attenuation coefficients are obtained through the least square (LS) method. To alleviate the impact of THz channel fading peaks caused by molecular absorption, estimates on multiple sub-bands are utilized for location estimation. Simulation results validate the superiority of the proposed NF-JCEL algorithm to the conventional far-field algorithm and show that higher resolution accuracy can be obtained by the proposed algorithm.