Low‐complexity MMSE‐IRC algorithm for uplink massive MIMO systems

Abstract

In uplink massive multiple‐input multiple‐output (MIMO) systems, the conventional minimum mean square error‐interference rejection combining (MMSE‐IRC) signal detection algorithm needs to compute the inverse of the interference and noise covariance matrix, which incurs high computational complexity, especially when the number of antennas is large. A low‐complexity MMSE‐IRC signal detection algorithm based on the eigenvalue decomposition of the interference and noise covariance matrix is proposed. The proposed algorithm exploits a dimension‐reduction technique to reduce the computation‐intensive of the matrix inversion compared with the conventional algorithm. Meanwhile, the proposed algorithm is shown to be equivalent to the conventional MMSE‐IRC algorithm under the assumption of uncorrelated interference and noise. Analysis and simulation results show the effectiveness of the proposed algorithm.