Pilot decontamination in massive multiuser MIMO systems based on low‐rank matrix approximation

Abstract

In multi-cell massive multiuser multi-input multi-output (MU-MIMO) systems, the channel estimation performance is degraded by the pilot contamination problem. This effect occurs when non-orthogonal pilot sequences are reused by other users in the adjacent cells. In this study, two channel estimation methods based on low-rank matrix approximation technique are proposed to mitigate pilot contamination problem in time division duplex multi-cell massive MU-MIMO systems. In the first method, the massive MU-MIMO channel estimation is formulated as the nuclear norm (NN) optimisation problem and solved by using a novel estimation algorithm proposed in this study. In the second method, the iterative weighted NN (IWNN) is proposed to improve the NN estimation performance. Consequently, the regularisation parameter of both optimisation methods is selected based on the cross-validation curve method. The simulation results show that both proposed methods outperform the traditional least square method in terms of the normalised mean square error. Moreover, the IWNN estimation method demonstrates substantial improvement over the NN estimation method in the presence of strong pilot contamination problem.