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A channel deflation approach for the blind deconvolution of a complex FIR channel with real input

In this paper we present a novel second-order statistics method for the blind deconvolution of a real signal propagating through a complex channel. The method is computationally very efficient since it involves only one SVD computation for the time-delayed output covariance matrix. No other optimization is involved. The subspaces corresponding to the left and right singular value matrices can be used to “deflate” the channel: projecting the output signal on either subspace reduces the filter length to 1, thus source reconstruction is simplified. The method is suitable for any channel length and it offers performance improvement compared to well established methods.