Spatial Channel Covariance Estimation and Two-Timescale Beamforming for IRS-Assisted Millimeter Wave Systems

We consider the problem of spatial channel covariance matrix (CCM) estimation for intelligent reflecting surface (IRS)-assisted millimeter wave (mmWave) communication systems. Spatial CCM is essential two-timescale beamforming in IRS-assisted systems; however, estimating challenging due to passive nature elements and large size resulting from massive IRS. In this paper, we propose a method by exploiting low-rankness as well positive semi-definite (PSD) 3-level Toeplitz structure CCM. Estimation formulated semidefinite programming (SDP) an alternating direction multipliers (ADMM) algorithm developed. Our analysis shows that proposed theoretically guaranteed attain reliable estimate with sample complexity much smaller than dimension Thus can help achieve significant training overhead reduction. Simulation results are presented illustrate effectiveness our performance scheme based on estimated