Low-complexity multiuser detection in massive spatial modulation MIMO

Abstract

In this paper, we research the multiuser detection (MUD) in a new massive Spatial Modulation Multiple Input Multiple Output (SM-MIMO) system, where the Base Station (BS) is equipped with massive antennas, and every User Equipment (UE) has multiple Transmit Antennas (TAs) but only one Radio-Frequency (RF) chain. In the uplink, UEs transmit data to the BS over frequency selective channels by the Cyclic-Prefix Single-Carrier (CP-SC) SM. We construct a new Generalized Approximate Message Passing Detector (GAMPD), and analyzes its mean square error performance theoretically by the State Evolution (SE) tool. By exploiting both the prior probability distribution and sparsity of the transmitted signal, GAMPD shows superior detection performances and works well even when the number of TAs at the UEs is larger than the number of BS antennas. GAMPD calls for parallelized matrix-vector multiplication as the most complex operation, so it has low computational complexity and is suitable for hardware implementation. Simulation results show that GAMPD outperforms the linear detectors significantly, and is analyzed by SE successfully. In addition, compared to the classical massive MIMO, massive SM-MIMO shows better detection performance and higher spectral efficiency.