Pseudo-channel matrix truncation based spatial correlation mitigation in massive MIMO

Abstract

Massive multiple-input multiple-output (MIMO), a technique that can greatly increase spectral efficiency (SE) of cellular networks, has attracted significant interests in recent years. One of the major limitations of massive MIMO systems is pilot contamination, which will deteriorate the SE. The superimposed pilot-based scheme has been proved to be a viable method for pilot contamination reduction. However, it cannot break through another limitation of massive MIMO, i.e., spatial correlation. In addition, it will also lead to interference between the pilot and user data since they are imposed together. In this paper, we try to tackle these two issues, which will be described as follows. Firstly, a column-wise asymptotically orthogonal matrix, named as pseudo-channel matrix, is developed by orthogonalization of received signal. To recover the information about the large-scale fading (LSF) coefficients, the pseudo-channel matrix is truncated according to the cardinality of adjacent users set (CAUS). By this means, spatial correlation can be mitigated effectively. Secondly, robust independent component analysis (RobustICA) is used to reduce the interference caused by user data, and as a result the system performance can be further improved. Numerical simulation results demonstrate the effectiveness of the proposed method.