Pilots Optimization and Surface Area Effects on Channel Estimation in RIS Aided MIMO System

Abstract

Reconfigurable intelligent surface (RIS) is an emerging tool for 5G and wireless communication technologies that have attracted researchers' interest. However, the passive nature and the high number of reflecting elements in RIS result in a large pilot overhead, which makes channel estimation challenging in multi-user multiple-input multiple-output (MU-MIMO) wireless communication systems. Previous works have shown an improvement in reducing the pilot overhead by exploiting the structured sparsity in rows and columns, which was further improved by compensating offset among users in angular cascaded channels of RIS aided system. To further reduce the pilot overhead, we analyze and adopt coherence-optimized pilots for channel estimation and propose an algorithm to analyze the combined effect of low-coherence pilots with an optimum size of RIS elements for a given number of users, transmit antennas, and normalized error threshold performance. The simulation results illustrate better NMSE performance as compared to contemporary techniques.

Keywords

• channel estimation
• compressed sensing
• reconfigurable intelligent surface
• mm-wave mimo communication
• sparse channel