Sparsity-Exploiting Detection of Large-Scale Multiuser GSM-MIMO Signals Using FOCUSS

Abstract

In this paper, we investigate the detection problem in large-scale multiuser generalized spatial modulation MIMO (GSM-MIMO) systems on the uplink. The inherent sparsity present in multiuser GSM-MIMO signals enables us to view the signal detection problem as one of sparse signal recovery in underdetermined systems using compressed sensing techniques. Accordingly, we propose a FOCUSS (FOCal Underdetermined System Solver) based algorithm for GSM-MIMO signal detection. Viewing the FOCUSS based detection as a sequence of weighted $l_2$-norm minimizations, we compare the performance of the FOCUSS based detection with that of the classical $l_2$-norm minimizer, the MMSE detection. Simulation results show that the FOCUSS based detection beats the MMSE detection by about 10 dB at $10^{-3}$ BER at a system loading factor of 1.1. This SNR gain of FOCUSS based detection over MMSE detection is found to increase with increasing system loading factors. Also, the FOCUSS based detection is shown to achieve better performance compared to OMP and CoSaMP based detection.