Flexible Intelligent Metasurface for Downlink Communications under Statistical CSI

TL;DR

This paper explores the use of flexible intelligent metasurfaces (FIM) in downlink multiuser MISO systems, optimizing average spectral efficiency with statistical CSI, and demonstrating significant gains over traditional rigid antenna arrays in correlated channels.

Contribution

It introduces a novel FIM optimization algorithm based on statistical CSI, departing from prior reliance on instantaneous CSI, and derives the spatial correlation matrix for FIM-aided transmitters.

Findings

FIM systems outperform RAA in highly correlated channels.

Performance gain diminishes with weak channel correlation.

Proposed iterative optimization improves spectral efficiency.

Abstract

Flexible intelligent metasurface (FIM) is a recently developed, groundbreaking hardware technology with promising potential for 6G wireless systems. Unlike conventional rigid antenna array (RAA)-based transmitters, FIM-assisted transmitters can dynamically alter their physical surface through morphing, offering new degrees of freedom to enhance system performance. In this letter, we depart from prior works that rely on instantaneous channel state information (CSI) and instead address the problem of average sum spectral efficiency maximization under statistical CSI in a FIM-assisted downlink multiuser multiple-input single-output setting. To this end, we first derive the spatial correlation matrix for the FIM-aided transmitter and then propose an iterative FIM optimization algorithm based on the gradient projection method. Simulation results show that with statistical CSI, the FIM-aided system provides a significant performance gain over its RAA-based counterpart in scenarios with strong spatial channel correlation, whereas the gain diminishes when the channels are weakly correlated.