A RIS-Assisted MUSIC-Like Single-Channel Blind Direction-of-Arrival Estimation Method

Existing reconfigurable intelligent surface (RIS)-based single-channel direction of arrival (DOA) estimation methods have overlooked the limitations of the maximum RIS state change rate, which leads to the problem of unknown symbols randomly perturbing the DOA estimation. To address the issue above, this letter proposes a RIS-assisted MUSIC-like (RIS-ML) single-channel blind DOA estimation method. Precisely, to decouple the RIS state change rate and DOA estimation, a RIS-ML algorithm and a dual-function RIS state matrix are proposed for blind DOA estimation. Then, the atomic norm minimization (ANM) algorithm is used to solve the DOA estimation problem. Simulation results have shown that the proposed method can effectively solve the blind DOA estimation problem, achieving symbol error rate (SER) of
$10^{-4}$
and RMSE of 0.1° respectively, in the case of limited RIS state change rate and unknown communication signals.