Channel Estimation in RIS-Aided mmWave Wireless Systems Using Matching Pursuit With Phase Rotation

Reconfigurable Intelligent Surface (RIS) is considered one of the most promising technologies for the next generation of wireless communication networks. Despite its great potential, RIS faces new challenges in integrating efficiently into wireless networks, including reflection optimization, channel estimation (CE), and optimization of deployment locations. This paper presents and analyzes a CE solution in RIS-assisted systems using compressive sensing techniques. The steering vector and the complex channel gains of the base station (BS)-RIS/user equipment (UE)-RIS links are estimated separately by using the matching pursuit with phase rotation (MP-PR) by deploying a few active elements at the RIS panel. The performance and complexity of the proposed method are comprehensively analyzed in different scenarios and compared against those of several other related methods in the literature. Numerical results show the effectiveness of the proposed method, which achieves better (or at least very similar) performance compared to other relevant techniques but with a significant decrease in computational complexity.