Journal ArticleSpatial Correlation-Aware Opportunistic Beamforming in IRS-Aided Multi-User SystemsYashvanth, L; Murthy, Chandra R; Rao, Bhaskar DThis paper addresses the high overheads associated with intelligent reflecting surface (IRS) aided wireless systems. By exploiting the inherent spatial correlation among the IRS elements, we propose a novel approach that randomly samples the IRS phase configurations from a carefully designed distribution and opportunistically schedules the user equipments (UEs) for data transmission. The key idea is that when IRS configuration is randomly chosen from a channel statistics-aware distribution, it will be near-optimal for at least one UE, and upon opportunistically scheduling that UE, we can obtain nearly all the benefits from the IRS without explicitly optimizing it. We formulate and solve a variational functional problem to derive the optimal phase sampling distribution. We show that, when the IRS phase configuration is drawn from the optimized distribution, it is sufficient for the number of UEs to scale exponentially with the rank of the channel covariance matrix, not with the number of IRS elements, to achieve a given target SNR with high probability. Our numerical studies reveal that even with a moderate number of UEs, the opportunistic scheme achieves near-optimal performance without incurring the conventional IRS-related signaling overheads and complexities.IEEE2025-01-0110631366IEEE Wireless Communications Letters1 to 12162-2337https://doi.org/10.1109/LWC.2025.35882572225617Intelligent reflecting surfaces (IRS), spatial correlation, opportunistic scheduling, multi-user diversityNational Science Foundation