Multiple Symbol Differential Approximate Maximum-Likelihood Detection for Unitary Space-Time Modulation in Continuous Fading

Recently, a multiple symbol differential sphere decoding (MSDSD) algorithm for unitary space-time modulation over quasi-static channel has been proved to achieve the performance of maximum-likelihood (ML) detection with relatively low complexity. However, an error floor occurs if the algorithm is applied to rapid-fading channels. Based on the assumption of continuous fading, a multiple symbol differential approximate automatic sphere decoding (MSDAASD) algorithm is developed by incorporating a recursive form of an approximate ML metric into automatic sphere decoding. The proposed algorithm is suitable for arbitrary unitary constellations and eliminates the error floor in MSDSD. Compared with decision-feedback detection under the same assumption, MSDAASD achieves similar performance to ML detection with much lower complexity at moderate to high signal-to-noise ratios