Multi-IRS-Assisted mmWave MIMO Communication Using Twin-Timescale Channel State Information

Abstract

To reduce the computational complexity and channel estimation overhead for multi-intelligent reflecting surface (IRS)-assisted millimeter wave (mmWave) multiple-input multiple-output (MIMO) communication, we consider a joint design of the hybrid precoders at the base station and the passive precoders at the IRSs to maximize the ergodic spectral efficiency by exploiting the twin-timescale channel state information (CSI). Specifically, the digital precoder is designed according to the instantaneous CSI of a reduced-dimensional assist channel matrix, while the IRS passive reflection coefficient matrices and the analog precoder are optimized using the statistical CSI of all links. However, such a design problem is challenging to solve due to the non-convexity and the twin timescale. This work proposes efficient algorithms to jointly design the precoders, where the update of the IRS reflection coefficient matrices is independent of the hybrid precoders and the design of the analog precoder is independent of the digital precoder. Simulation results demonstrate the effectiveness of the proposed algorithms and provide the application scenes of the fully-connected and subarray-connected architectures. The results also show that the ergodic spectral efficiency for the fully-connected architecture using the twin-timescale CSI can approach that using the existing CSI schemes with less channel estimation overhead and computational complexity.