Low-complexity soft ML detection for generalized spatial modulation

• DOI: 10.1016/j.sigpro.2022.108509
• Publication Date: 2022-02-16T15:58:59Z
• Authors: M. Ángeles Simarro; Víctor M. García-...; F.J. Martínez-Zal...; Alberto Gonzalez
• Keywords: GSM; Clipping (morphology)

Generalized Spatial Modulation (GSM) is a recent Multiple-Input Multiple-Output (MIMO) scheme, which achieves high spectral and energy efficiencies. Specifically, soft-output detectors have key role in achieving the highest coding gain when an error-correcting code (ECC) used. Nowadays, Maximum Likelihood (ML) detection MIMO-GSM systems leads to computational complexity that unfeasible for real applications; however, it important develop low-complexity decoding algorithms provide reasonable simulation time order make performance benchmark available systems. This paper presents three achieve ML performance. In first algorithm, different strategies are implemented, such as preprocessing sorting step avoid exhaustive search. addition, clipping of extrinsic log-likelihood ratios (LLRs) can be incorporating this algorithm give lower cost version. The other two proposed only used with results show significant saving cost. Furthermore allows wide-trade-off between by adjusting parameter.