Analysis of Semi-Blind Channel Estimation in Multiuser Massive MIMO Systems With Perturbations

In the massive multiple-input multiple-output (MIMO) systems, pilot contamination and signal perturbation are two important issues in the semi-blind channel estimation methods. To evaluate the effects of pilot contamination and signal perturbation, the covariance matrix of the received signal should be obtained. In specific, the eigenvectors associated with the K largest eigenvalues of the ideal covariance matrix, contain the subspace information of the desired signals, in which the interference and partial noise are eliminated because of asymptotic orthogonality of the fading matrix. Since it is quite difficult to acquire the ideal covariance matrix, the sample covariance matrix calculated by the finite data samples is adopted to approximate the ideal covariance matrix in practice. However, the gap between the ideal covariance matrix and the sample covariance matrix leads to signal perturbation. In this paper, the perturbation analysis of a semi-blind channel estimation in the massive MIMO systems is presented. Simulation results verify the validity of our perturbation analysis. Furthermore, it is demonstrated by simulations that signal perturbation affects system performance by reshaping the eigenvectors and eigenvalue distributions of the target cell and interfering cells.