A deterministic approach to blind equalization

Conventional blind channel identification algorithms are based on channel outputs and the known probabilistic model of a channel input. In practical applications, however, the input statistical model may not be known, or there may not be sufficient data to obtain accurate enough estimates of certain statistics. In this paper, we consider the system input to be an unknown deterministic signal and study the problem of blind identification of a channel which can be decomposed into multichannel FIR systems driven by a input signal. A new deterministic blind identification algorithm based solely on the system outputs are proposed. Necessary and sufficient identifiability conditions concerning the channel and the deterministic input signal are also presented