RIS-Aided User Localization Design with Multiple Signal Classification Based Orthogonal Subspace Projection
Wanning Meng, Zheng Dong, Yong Zhou, Lei Li, Zhi Liu · 2024
We consider a reconfigurable intelligent surface (RIS)-aided multiuser localization systems. To handle the localization problems of all the users, we propose a multiple signal classification based orthogonal projection (MUSIC-OP) algorithm. Specifically, we apply the space alternating gener-alized expectation-maximization (SAGE) algorithm to estimate the channel from RIS to the base station (BS) with the aid of a known anchor. By projecting the received signal onto the orthogonal subspace of the cascaded channel created by the RIS and the direct channel between BS and all users, respectively, we can separate the received signal transmitted from the cascaded channel and the direct links from their superimposed signal vectors. Then, the MUSIC algorithm is employed to estimate the direction of arrival (DOA) of each user relative to both the BS and RIS, followed by subsequent localization processes. Simulation results show that the proposed MUSIC-OP algorithm has a better DOA estimation performance compared to the deterministic maximum likelihood (DML) and orthogonal matching pursuit (OMP) algorithms.