📝 SummarXiv

Abstract

Reconfigurable intelligent surfaces (RISs) are emerging as key enablers of reliable industrial automation in the millimeter-wave (mmWave) band, particularly in environments with frequent line-of-sight (LoS) blockage. While prior works have largely focused on theoretical aspects, real-time validation under user mobility remains underexplored. In this work, we propose and experimentally evaluate an adaptive beamforming algorithm that enables RIS reconfiguration via a low-rate feedback link from the mobile user equipment (UE) to the RIS controller, operating without requiring UE position knowledge. The algorithm maintains the received signal power above a predefined threshold using only a single-bit comparison of received power levels. To analyze the algorithms performance, we establish a simulation-based Monte Carlo (MC) optimization benchmark that assumes full UE position knowledge, accounts for practical hardware constraints, and serves as an upper bound for performance evaluation. Using a hexagonal RIS with 127 elements and 1-bit phase quantization at 23.8 GHz, we validate the proposed approach in a semi-anechoic environment over a 60 cm by 92 cm area. The results demonstrate that the single-bit feedback-driven algorithm closes much of the performance gap to the MC upper bound while achieving up to 24 dB gain in received power compared to an inactive RIS baseline. These findings highlight the practical potential of feedback-based adaptive RIS control for robust mmWave non-line-of-sight (NLoS) communication with mobile users.