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-Nr received data block by a single Hermitian matrix (sized Nt × Nt) inversion, is especially preferable in Massive MIMO up-link applications where the number of transmit antennas Nt from each end terminal is much less than the number of receive antennas Nr 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(Nt 3) to O(Nt 2). 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.