Transmission design for the XL-RIS-aided massive MIMO system with visibility regions

This study proposes a two-timescale transmission scheme for extremely large-scale reconfigurable intelligent surface aided (XL-RIS-aided) massive multi-input multi-output (MIMO) systems in the presence of visibility regions (VRs). The beamforming of base stations (BSs) is designed based on rapidly changing instantaneous channel state information (CSI), while the phase shifts of RIS are configured based on slowly varying statistical CSI. Specifically, we first formulate a system model with spatially correlated Rician fading channels and introduce the concept of VRs. Then, we derive a closed-form approximate expression for the achievable rate and analyze the impact of VRs on system performance and computational complexity. Then, we solve the problem of maximizing the minimum user rate by optimizing the phase shifts of RIS through an algorithm based on accelerated gradient ascent. Finally, we present numerical results to validate the performance of the considered system from different aspects and reveal the low system complexity of deploying XL-RIS in massive MIMO systems with the help of VRs.