Compressive sensing based multiuser detector for massive MBM MIMO uplink

Abstract

Media based modulation (MBM) is expected to be a prominent modulation scheme, which has access to the high data rate by using radio frequency (RF) mirrors and fewer transmit antennas. Associated with multiuser multiple input multiple output (MIMO), the MBM scheme achieves better performance than other conventional multiuser MIMO schemes. In this paper, the massive MIMO uplink is considered and a conjunctive MBM transmission scheme for each user is employed. This conjunctive MBM transmission scheme gathers aggregate MBM signals in multiple continuous time slots, which exploits the structured sparsity of these aggregate MBM signals. Under this kind of scenario, a multiuser detector with low complexity based on the compressive sensing (CS) theory to gain better detection performance is proposed. This detector is developed from the greedy sparse recovery technique compressive sampling matching pursuit (CoSaMP) and exploits not only the inherently distributed sparsity of MBM signals but also the structured sparsity of multiple aggregate MBM signals. By exploiting these sparsity, the proposed CoSaMP based multiuser detector achieves reliable detection with low complexity. Simulation results demonstrate that the proposed CoSaMP based multiuser detector achieves better detection performance compared with the conventional methods.