Multipath Assisted Near-Field Localization for STAR-RIS Based mmWave Systems

Simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is able to perform reflection and refraction of the incident signals simultaneously, making it a promising technology for omnidirectional localization. In this work, we study a STAR-RIS based millimeter-wave (mmWave) localization system in the near field. In particular, we exploit the multipath components (MPCs) as signals emitted from a virtual STAR-RIS and propose a multi-stage localization algorithm. Specifically, in the initialization stage, we present a practical two-step localization method to obtain coarse estimates of UE positions, based on the second-order Fresnel approximation of the near-field channels. In the optimization stage, to effectively leverage the MPCs for localization performance improvement, we propose to add signal weights to the received signals. Then, the signal weights, STAR-RIS energy splitting (ES) coefficients and phase shifts are jointly optimized to minimize the Cramér-Rao lower bound (CRLB). Finally, in the refinement stage, the localization accuracy is further improved based on the information obtained during the first two stages. Simulation results demonstrate the effectiveness of the proposed multipath assisted localization algorithm and show that STAR-RIS surpasses conventional RIS in the omnidirectional localization scenario.