Abstract—Generalized spatial modulation was recently proposed, in which only part of the transmit antennas are activated to send the same complex symbol. Compared to Spatial Modulation (SM), it can offer spatial diversity. Moreover, it is no longer limited to the number of the transmit antennas. In this letter, a low complexity detection scheme is presented, which can achieve a near Maximum-Likelihood (ML) performance and reduce the complexity compared to ML. In the proposed algorithm, the antenna index is ordered first based on the Hermitian angle between the received vector y and the combined channel vector h_j . With the antenna index list, the constellation symbol can be estimated by calculating the difference between the normalized projection of received symbol in the direction of combined channel and the actual transmitted symbols. We can make a tradeoff between the performance and the complexity by changing the number of the candidate transmit antennas. The simulation results show that the proposed algorithm can achieve a near-ML performance with lower complexity.

Index Terms—Generalized spatial modulation, low complexity, maximum likelihood, multiple-input-multiple-output


Cite: Yang Jiang, Yingjie Xu, Yunyan Xie, Shaokai Hong, and Xia Wu, “Low-Complexity Detection Scheme for Generalized Spatial Modulation," Journal of Communications, vol. 11, no. 8, pp. 726-732, 2016. Doi: 10.12720/jcm.11.8.726-732