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This 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. 

This paper addresses the mitigation of spatial-wideband (SW) and the resulting beam-split (B-SP) effects in intelligent reflecting surface (IRS)-aided wideband systems. The SW effect occurs when the signal delay across the IRS aperture exceeds the system’s sampling duration, causing the user equipment’s (UE) channel angle to vary with frequency. This leads to the B-SP effect, wherein the IRS cannot coherently beamform to a given UE over the entire bandwidth, reducing array gain and throughput. We first show that partitioning a single IRS into multiple smaller IRSs and distributing them in the environment can naturally mitigate the SW effect (and hence the B-SP effect) by parallelizing the spatial delays and exploiting angle diversity benefits. Next, by determining the maximum number of elements at each smaller IRS to limit B-SP effects and analyzing the achievable sum-rate, we demonstrate that our approach ensures a minimum positive rate over the entire bandwidth of operation. However, distributed IRSs may introduce temporal delay spread (TDS) due to the differences in the path lengths through the IRSs and this may reduce the achievable flat channel gain. To minimize TDS and maintain the full array gain, we show that the optimal placement of the IRSs is on an ellipse with the base station (BS) and UE as the focal points. We also analyze the impact of the optimal IRS placement on TDS and throughput for a UE that is located within a hotspot served by the IRSs. Finally, we illustrate that distributed IRSs enhance angle diversity, which exponentially reduces the outage probability due to B-SP effects as the number of IRSs increases. Numerical results validate the efficacy and simplicity of our method compared to the existing solutions.