The problem of blind equalization and channel estimation for partial-response signals (PRS) is considered. Three approaches are investigated; two of them exploit the prior knowledge of the PR code, and the third approach does not. We propose a constrained optimization approach involving a quadratic cumulant matching criterion where the coding structure of the transmitted signal is assumed to be a priori known. The other two approaches exploit the Godard blind equalizer. Computer simulation results using 16-QAM signals, and duobinary and modified duobinary PR codes, show that the constrained optimization approach yields the best performance as measured via the probability of symbol detection error.

A typical assumption made in most of the existing blind channel estimation and/or equalization approaches is that the signal input to the digital communications channel is i.i.d. One important case where this is not true is that of correlative coded, or partial-response (PR), signals where a controlled amount of ISI (intersymbol interference) is introduced at the transmitting end in order to eliminate any need for "excess" bandwidth. We consider the problem of blind equalization for such signals. We propose a constrained optimization approach where the coding structure of the transmitted signal is assumed to be a priori known. Computer simulation results using 16-QAM signals, and duobinary and modified duobinary PR codes, are presented where the proposed approach is compared with two other possible approaches.>