Correlation-Aware Adaptive Element Grouping for Discrete-Phase RIS in High-Mobility Scenarios

Abstract

This letter proposes an adaptive element grouping method for discrete-phase reconfigurable intelligent surfaces (RISs) serving a high-mobility user equipment (UE) to maximize the average net spectral efficiency. A drift-aware channel state information (CSI) aging model is derived for the RIS-to-UE link, enabling pilot refreshing, CSI prediction, and error covariance characterization. With pilot-training and RIS-reconfiguration overhead included, a two-timescale design is developed: slow-timescale grouping exploits spatial correlation, whereas fast-timescale beamforming and discrete-phase optimization use predicted CSI while retaining residual inter-group coupling. Simulations show higher net spectral efficiency than existing grouping schemes, especially under high mobility and large-scale RISs.