Low Complexity Overloaded MIMO Detection Based on Belief Propagation with MMSE Pre-Cancellation

Abstract

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) systems. In overloaded MIMO systems, the loops in the factor graph degrade the demodulation performance of BP. Therefore, the proposed scheme applies MMSE pre-cancellation prior to BP and reduces the number of 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 to suppress the residual interference and the noise after MMSE pre-cancellation. Numerical results obtained through computer simulation show that the proposed scheme achieves better bit error rate (BER) performance than BP without MMSE pre-cancellation. The proposed scheme improves the BER performance by 2.9-5.6dB at a BER of 5.0×10^-3 compared with conventional BP. Numerical results also show that MMSE pre-cancellation reduces the complexity of BP by a factor of 896 in terms of the number of multiplication operations.