Flexible Intelligent Metasurface for Downlink Communications under Statistical CSI

2025-12-28

AI Summary

This work addresses the downlink multi-user multiple-input single-output (MU-MISO) scenario for 6G wireless systems under statistical channel state information (CSI) only, aiming to maximize average sum spectral efficiency. Method: Leveraging the dynamic mechanical deformation capability of flexible intelligent metasurfaces (FIMs), we establish a novel spatially correlated FIM channel model that explicitly couples statistical CSI with physical surface deformation. We further propose a gradient-projection-based joint beamforming and FIM configuration optimization algorithm, eliminating reliance on instantaneous CSI and rigid antenna arrays. Contribution/Results: Experiments demonstrate that the proposed scheme significantly outperforms conventional rigid RIS baselines in strongly spatially correlated channels, while maintaining stable convergence in weakly correlated regimes. This work validates the effectiveness and robust adaptability of FIMs under imperfect, low-overhead CSI conditions, establishing a new paradigm for statistical-domain reconfigurable intelligent surface (RIS) design.

Technology Category

• Search and Optimization: Metareasoning and Metaheuristics
• Intelligent Robots: Multi-Robot Systems
• Multiagent Systems: Mechanism Design

Application Category

• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG

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.

Problem

• Maximizes average sum spectral efficiency using statistical CSI
• Optimizes flexible intelligent metasurface for downlink multiuser MISO
• Addresses performance in spatially correlated versus uncorrelated channels

Innovation

• Flexible metasurface dynamically alters physical shape
• Optimization algorithm uses statistical channel state information
• Gradient projection method maximizes average spectral efficiency