Abstract
Tugnait, Chi and Chen proposed multi-input multi-output inverse filter criteria (MIMO-IFC) using higher-order statistics (HOS) for blind deconvolution of MIMO linear time-invariant (LTI) systems. Chi and Chen also proposed a property of nonlinear relationship between the optimum inverse filter associated with MIMO-IFC and the MIMO minimum mean square error (MIMO-MMSE) equalizer. In this paper, based on the nonlinear relationship, an iterative single-input multi-output (SIMO) blind channel estimation (BCE) algorithm and a time delay estimation (TDE) algorithm using HOS are proposed with a given set of non-Gaussian measurements. The former is a fast FFT-based algorithm for joint estimation of magnitude response and phase response of SIMO systems and the latter estimates P-1 time delays from the phase information of single-input P-output (P>=2) system leading to a closed-form solution of time delay estimates using the optimum inverse filter associated with MIMO-IFC. Some simulation results are presented to support the efficacy of the proposed SIMO BCE and TDE algorithms.