Low Complexity Belief Propagation based MIMO Detection with MMSE Pre-cancellation for Overloaded MIMO systems

In this paper, the application of minimum mean square error (MMSE) pre-cancellation prior to belief propagation (BP) is proposed as a detection scheme for overloaded multiple-input multiple-output (MIMO). In overloaded MIMO, the loops in a factor graph deteriorate the demodulation performance with BP. Therefore, the proposed scheme applies the MMSE pre-cancellation prior to BP and reduces the number of the loops. Furthermore, it is applied to the selected transmit and receive nodes so that the condition number of an inverse matrix in the MMSE weight matrix is minimized in order to suppress the residual interference and the noise after the MMSE precancellation. It is shown by numerical results obtained through computer simulation that the proposed scheme achieves better bit error rate (BER) performance than BP without the MMSE pre-cancellation. The proposed scheme improves the BER performance by 4.6-5.0 dB at a BER of 5.0 × 10-3 as compared with conventional BP. Numerical results also shows that the MMSE pre-cancellation reduces the complexity in BP by a factor of 1/896 in terms of the number of multiplication operations.