Design of decision feedback equalizer with short training sequence

An exact convergence analysis of the LMS-DFE equalizer during the training phase is derived by taking into account the finite alphabet context of data transmission. This allow us to determine the shortest training sequence that allows one to reach a given MSE and to propose a convergence strategy for the blind decision directed (DD) algorithm. This theta yields a semi-blind DD algorithm.