Low Complexity Signal Detector Based On Ssor Iteration For Large-Scale Mimo Systems

The scaling up of antennae and terminals in large-scale multiple-input multiple-output (MIMO) systems helps increase the spectral efficiency at the penalty of prohibitive computational complexity. In conventional linear detection such as the minimum mean square error (MMSE) signal detection, the high complexity is mainly caused by solving the inversion of random matrix, especially in large-scale MIMO systems. In order to reduce the complexity of the matrix inversion, we proposed a low-complexity MMSE detection scheme based on symmetric successive over relaxation (SSOR) method, referred to as MSSD method. The proposed method exploits the channel hardening phenomenon, which means the off-diagonal terms of the HHH matrix become increasingly weaker compared to the diagonal terms as the size of the channel gain matrix H increases. In addition, we point out that the channel estimation scheme used in channel hardening exploiting message passing receiver (CHEMP) is very suitable for the MSSD algorithm. For the considered large MIMO settings, simulation results show that the performance of the MSSD algorithm is very close to the classical MMSE detection algorithm with a small number of iterations.