Iterative equalization with adaptive soft feedback

In this letter, a novel equalization algorithm applying soft-decision feedback and designed for binary transmission is introduced. In contrast to conventional decision-feedback equalization (DFE), iterations are necessary, because a simple matched filter serves as feedforward filter, which collects signal energy, but creates noncausal intersymbol interference. The rule for generating soft decisions is adapted continuously to the current state of the algorithm. In most cases, standard DFE methods are clearly outperformed. For a class of certain channel impulse responses, performance of maximum-likelihood sequence estimation is attained, in principle. The high performance of the scheme is explained using results from neural network theory