NONMINIMUM-PHASE CHANNEL DECONVOLUTION USING THE COMPLEX CEPSTRUM OF THE CYCLIC AUTOCORRELATION

New discrete time blind deconvolution methods are proposed for nonmini mum phase linear channels driven by cyclostationary inputs. The method s rely exclusively on second-order statistics and do not impose any co nstraints on the distribution of the channel input as in the case of m ethods based on higher-order statistics. The output of the channel is fractionally sampled and then the complex cepstrum of the cyclic autoc orrelation is obtained. It is shown that this complex cepstrum preserv es nonminimum phase information and thus the identification of nonmini mum phase channels is possible. Practical constraints in the implement ation of the methods and channel identifiability conditions are discus sed. The applicability of the methods to both channel identification a nd fractionally spaced linear and DFE equalization is described and ve rified by means of computer simulations.