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The detection problem for the Multipleaccess Spatial modulations(M-SM) is investigated in this paper, where multiple transmitters adopting spatial modulation communicate to the receiver at the same time.The optimal Maximum-likelihood(ML) detection suffers from the high computational complexity, while Sphere decoding(SD) can not reduce the complexity effectively because of the multiple active antennas in M-SM. In order to avoid the high complexity, a Space-alternating generalized expectation-maximization(SAGE) algorithm aided List-pro jection(S-LP) detector is proposed and applied to M-SM systems. The received signal vector is firstly projected onto the subspaces spanned by the columns of channel matrices corresponding to the possible active antennas. Then some combinations of antenna indices with the largest pro jections are selected as candidate index sets,based on which, a modified SAGE algorithm is applied to update the candidate symbols. Both analysis and simulation results show that the proposed S-LP detector achieves a near-optimum performance with a significantly reduced complexity compared with ML and SD detection.
The detection problem for the Multiple Access Spatial modulations (M-SM) is investigated in this paper, where multiple transmitters perform spatial modulation communicate to the receiver at the same time. The optimal Maximum-likelihood (ML) detection suffers from the high computational complexity, while Sphere decoding (SD) can not reduce the complexity effectively because of multiple active antennas in M-SM. In order to avoid the high complexity, a Space-alternating generalized expectation-maximization (SAGE) algorithm aided List-pro jection (S -LP) detector is proposed and applied to M-SM systems. The received signal vector is now projected onto the subspaces spanned by the columns of channel matrices corresponding to the possible active antennas. Then some combinations of antenna indices with the largest pro jections are selected as candidate index sets, based on which, a modified SAGE algorithm is applied to update the candidate symbols. Both analysis and simulation results show th at the proposed S-LP detector achieves a near-optimum performance with a significantly reduced complexity compared with ML and SD detection.