Cooperative Localization for Reconfigurable Intelligent Surface-Aided mmWave Systems

Abstract

Recently, reconfigurable intelligent surface (RIS) have been introduced not only to overcome communication blockages due to obstacles but also for high-precision localization of users in GPS denied environments, e.g., indoors, woods, and underground tunnels, etc. This paper studies the cooperative localization problem in an RIS-aided milimeter wave (mmWave) system, where the RIS is deployed to assist the localization of two users and the two users further cooperate to improve their localization performance. We first build the system model based on the uniform planar array (UPA) response of RIS. Then, the Fisher information matrix (FIM) and the Cramér-Rao lower bound (CRLB) for estimating the absolute user equipment (UE) position are derived. An efficient block coordinate descent (BCD)-based reflect beamforming design algorithm is proposed to minimize the CRLB. Finally, numerical results are presented to show that user cooperation can provide additional localization performance gain as compared to the case without cooperation and centimeter-level positioning accuracy can be achieved by utilizing a large number of reflecting elements and exploiting user cooperation.