A class of blind deconvolution and equalization algorithms for nonminimum phase multi-input multi-output systems

Abstract

A unified class of inverse filter criteria using two cumulants, which includes Wiggins' criterion, Donoho's criteria and Tugnait's criteria as special cases, has been proposed by Chi and Wu for blind deconvolution and equalization of real single-input single-output (SISO) linear time-invariant (LTI) systems. In this paper, we extend this class of (single channel) inverse filter criteria to a family of multistage and a family of single stage criteria for deconvolution and equalization of real (or complex) multi-input multi-output (MIMO) LTI systems with only non-Gaussian measurements. It can be shown that the two families of inverse filter criteria lead to perfect equalization for MIMO systems under some conditions. Some simulation results for the optimum inverse filter using gradient type iterative optimization algorithms were provided to support the proposed criteria. Finally, we draw some conclusions.