A low complexity iterative soft-decision feedback MMSE-PIC detection algorithm for massive MIMO

In MIMO applications, the minimum mean square error parallel interference cancellation (MMSE-PIC) based Soft-Input Soft-Output (SISO) detector has been widely adopted because of its low complexity and good bit error rate (BER) performance. In this paper, we firstly propose to use a Gaussian model based MMSE detection algorithm to implement MMSE-PIC with low complexity. This algorithm, which can detect a length-N_r received data block by a single Hermitian matrix (sized N_t × N_t) inversion, is especially preferable in Massive MIMO up-link applications where the number of transmit antennas N_t from each end terminal is much less than the number of receive antennas N_r in the Base Station. Then we derive a new method to calculate the matrix inversion by a linear combination of two matrices, which reduces the complexity from O(N_t³) to O(N_t²). At last, in order to improve the system performance for the first pass when there is no a priori information available, a self-iteration method is proposed and thus a system performance gain of 1dB to 2dB is achieved at the cost of modest complexity increase.