Uplink Channel Estimation for Multi-User MISO Systems Assisted by a Fluid Reconfigurable Intelligent Surface

TL;DR

This paper introduces a novel channel estimation framework for multi-user uplink systems aided by fluid reconfigurable intelligent surfaces, addressing uncertainties from element-position mismatches.

Contribution

It proposes a two-time-scale protocol and tensor-based estimation method to jointly estimate channels and motion-induced phase shifts in FRIS-assisted systems.

Findings

Achieves accurate channel estimation despite position uncertainties.

Demonstrates robustness of the proposed method through numerical simulations.

Provides a closed-form solution for joint channel and phase coefficient estimation.

Abstract

Fluid reconfigurable intelligent surfaces (FRISs) have recently emerged as a promising paradigm for wireless communications, wherein the reflecting elements can dynamically select their effective radiating positions from a dense preset grid, thereby introducing an additional degree of freedom. In contrast to conventional RIS architectures, FRISs can achieve spatial diversity with fewer physical elements. However, beyond the cascaded channel structure, FRIS-assisted systems are also affected by uncertainties arising from element-position mismatches caused by calibration inaccuracies or motion errors, which may degrade channel state information. To the best of our knowledge, channel estimation (CE) for FRIS-assisted systems under position uncertainty remains unexplored. To fill this gap, we propose a CE framework for a multi-user FRIS-assisted uplink system based on a two-time-scale FRIS configuration protocol that captures both reflection phase-shift and element-motion dynamics. By capitalizing on orthogonal pilot sequences and tensor modeling, we derive a closed-form solution that jointly estimates the individual channels and the motion-induced phase coefficients. Numerical results demonstrate notable performance in the presence of unknown position deviations.