Spatial Modulation Based Multiple Access for Ambient Backscatter Networks

Both spatial modulation (SM) and spatial multiple access (SMA) exploit spatial differences between antennas to implement modulation and multiple access. In this sense, this letter designs an SM-SMA system for ambient backscatter communication networks. SM activates a part of a tag's antennas to carry information, and thus decreases the interference between antennas in SMA. We then propose a modified-maximum likelihood (M-ML) detector to separate and obtain and the backscattered signal without the need of recovering the source signal. By exploiting the sparse characteristics of the SM-SMA signal, a multi-user sparse Bayesian learning (MSBL) based detector is further proposed to reduce the complexity of M-ML. The simulation results verify that SM-SMA achieves a lower bit error rate than SMA, and the MSBL based detector has a lower complexity than M-ML at the cost of increasing BER.