Joint Detection and Channel Estimation for MIMO-OTFS Systems

MIMO orthogonal time frequency space (OTFS) modulation is considered a promising communication technology for future ultra-high-speed vehicular scenarios. However, the high complexity channel estimator and low accuracy symbol detection algorithm hinder the development of OTFS modulation. Unlike the conventional receiver, channel estimation and symbol detection are relatively isolated, we design a novel joint receiver combining channel estimation and symbol detection exploiting a partial iterative feedback mechanism. Firstly, we take into account the effect of fractional Doppler and make it approximate gridding. Therefore, the channel estimation problem is transformed into a block sparse signal recovery problem, and an efficient sparse adaptive block orthogonal matching pursuit (ABOMP) algorithm is proposed. Secondly, we propose a low-complexity approximate message passing (AMP) algorithm, which provides a reference for selecting high-confidence data symbols and reduces the redundant calculation of multiple detections. Finally, a partial iteration feedback joint detection and channel estimation (JDCE) algorithm is proposed to further reduce the system bit error ratio (BER) and computational complexity. Comprehensive simulation experiments are conducted and demonstrate the effectiveness and superiority of the proposed algorithm.