Adaptive decision feedback equalization under parallel adaptation

In this paper, we first propose an alternative decision feedback equalizer (DFE) scheme to the DFE scheme of Labat, Macchi and Laot. Both schemes are broken into two distinct operation modes which feature a linear equalizer during acquisition and a DFE after the initial convergence has been achieved. While avoiding some potential problems with the latter DFE, our scheme achieves similar overall performance in terms of convergence speed and steady state error. A second contribution is the development of a strategy that simultaneously adapts the linear equalizer and the DFE in a parallel fashion such that the switch-over between modes is no longer necessary. Consequently, smoother and usually faster convergence is achieved as switching disruptions are reduced. This scheme is especially advantageous under noisy and severe conditions as supported by our simulations.