Simplified maximum likelihood-based detection schemes for M-ary quadrature amplitude modulation spatial modulation

In this study, the authors propose a simplified maximum likelihood (ML)-based detection scheme for N-t x N-r M-ary quadrature amplitude modulation (M-QAM) spatial modulation (SM) that is computationally less complex than the conventional ML detection scheme. Instead of searching for the transmit antenna index and transmitted symbol pair among all possible NtM pairs as in the ML-based optimal detection, the proposed simplified ML-based detection scheme firstly searches for pairs of transmit antenna index and transmitted symbol in level-one subsets which the transmitted signal most probably belongs to, and secondly searches for pairs of transmit antenna index and transmitted symbol in level-two subsets among those pairs in level-one subsets. We also extend the simplified ML-based optimal detection into multistage detection. Simulation results validate that the bit error rate (BER) performance of the proposed simplified ML-based detection schemes is almost the same as that of conventional ML detection with significant complexity reduction until a BER of 10(-6).