Low-Complexity Near-ML Detection Algorithms for NR-STAR-MQAM Spatial Modulation

In this study, the authors propose two low-complexity near-maximum-likelihood (ML) detection algorithms for spatial modulation (SM) systems, employing the new multiple-ring star-M-ary quadrature amplitude modulation (NR-STAR-MQAM) constellation. The proposed detectors exploit the specific orientation of NR-STAR-MQAM, in order to avoid searching across all constellation points. As a result, the computational complexity is independent of both the constellation size and the number of rings presented in NR-STAR-MQAM. In addition, these detectors are generalized and can be applied to the entire star-MQAM family. The Monte Carlo simulation results demonstrate that the proposed detection algorithms achieve the same average bit error rate (ABER) as ML detection for SM but at a much lower computational complexity. For example, in a 4 × 4, 2R-STAR-16QAM aided SM system, the proposed optimal and sub-optimal detectors achieve an 88.8% and 90.5% reduction in computational complexity, respectively, compared to the ML detector. Furthermore, the simulation results are supported by a closed-form union-bound theoretical ABER expression.