Rapid diagnostics of reconfigurable intelligent surfaces using space-time-coding modulation

TL;DR

This paper introduces a space-time coding-based diagnostic method for reconfigurable intelligent surfaces, enabling rapid fault detection and performance assessment crucial for large-scale deployment in next-generation wireless systems.

Contribution

It proposes a novel space-time coding strategy for RIS diagnostics, providing a reliable, efficient, and experimentally validated method for fault detection in RIS elements.

Findings

High diagnostic accuracy under various fault ratios

Effective fault detection even with high noise levels

Successful implementation on RIS prototypes in realistic scenarios

Abstract

Reconfigurable intelligent surfaces (RISs) have emerged as a key technology for shaping smart wireless environments in next-generation wireless communication systems. To support the large-scale deployment of RISs, a reliable and efficient diagnostic method is essential to ensure optimal performance. In this work, a robust and efficient approach for RIS diagnostics is proposed using a space-time coding strategy with orthogonal codes. The method encodes the reflected signals from individual RIS elements into distinct code channels, enabling the recovery of channel power at the receiving terminals for fault identification. Theoretical analysis shows that the normally functioning elements generate high power in their respective code channels, whereas the faulty elements exhibit significantly lower power. This distinction enables rapid and accurate diagnostics of elements' operational states through simple signal processing techniques. Simulation results validate the effectiveness of the proposed method, even under high fault ratios and varying reception angles. Proof-of-principle experiments on two RIS prototypes are conducted, implementing two coding strategies: direct and segmented. Experimental results in a realistic scenario confirm the reliability of the diagnostic method, demonstrating its potential for large-scale RIS deployment in future wireless communication systems and radar applications.