Sparse K-best detector for generalised space shift keying in large-scale multiple-input–multiple-output systems

In this study, the authors propose a low complexity detector for the generalised space shift keying (GSSK) in large-scale multiple-input-multiple-output systems. To be concrete, they propose a sparse K-best (SK) detector based on the breadth-first category of sphere detector (referred to K-best sphere decoding). The author´s detector is inspired by the fact that the GSSK signal is naturally a sparse zero-one vector since only a few antennas are activated at the transmitter. Different with the conventional K-best detector searching all the transmit antennas, their proposed SK detector investigates only a few promising candidates which are activated antennas at the transmitter. Overall, their proposed SK detector exploits not only the sparsity of the GSSK signal but also the constraint on its non-zero values. Therefore the restricted isometry property-based performance analysis shows that is effective in detecting the GSSK signal. Moreover, the empirical results show that their detector performs much better than the sparse algorithms-based normalised compressive sensing (NCS) detectors while exhibits only slightly higher complexity than the latter (the low-complexity orthogonal matching pursuit-based NCS detector).