Maximum-Likelihood Multiple Symbol Differential 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 is 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 Automatic Sphere Decoding (MSDASD) is developed by incorporating a recursive form of an ML metric in the automatic sphere decoding algorithm. The proposed algorithm is suitable for arbitrary unitary constellations and eliminates the error floor caused by MSDSD over fast fading channels. Compared with decision-feedback detection under the same assumption, MSDASD achieves performance of ML detection with much lower complexity at moderate to high signal-to-noise ratios.