Cumulant-based inverse filter criteria for MIMO blind deconvolution: properties, algorithms, and application to DS/CDMA systems in multipath

Tugnait and Chi and Chen proposed multi-input multi-output inverse filter criteria (MIMO-IFC) using higher order statistics for blind deconvolution of MIMO linear time-invariant systems. This paper proposes three properties on the performance of the MIMO linear equalizer associated with MIMO-IFC for any signal-to-noise ratio, including P1) perfect phase equalization property, P2) a relation to MIMO minimum mean square error (MIMO-MMSE) equalizer, and P3) a connection with the one obtained by MIMO super-exponential algorithm (MIMO-SEA) that usually converges fast but does not guarantee convergence for finite data. Based on P2), a fast algorithm for computing the theoretically optimum MIMO equalizer is proposed. Moreover, based on P3), a fast MIMO-IFC based algorithm with performance similar to that of the MIMO-SEA and with guaranteed convergence is proposed as well as its application to suppression of multiple access interference and intersymbol interference (ISI) for multiuser asynchronous DS/CDMA systems in multipath. Finally, some simulation results are presented to support the analytic results and the proposed algorithms.