On the Fast Convergence of DD-LMS DFE Using a Good Strategy Initialization
نویسندگان
چکیده
In wireless communication system, a Decision Feedback Equalizer (DFE) to cancel the intersymbol interference (ISI) is required. In this paper, an exact convergence analysis of the (DFE) adapted by the Least Mean Square (LMS) algorithm during the training phase is derived by taking into account the finite alphabet context of data transmission. This allows us to determine the shortest training sequence that allows to reach a given Mean Square Error (MSE). With the intention of avoiding the problem of ill-convergence, the paper proposes an initialization strategy for the blind decision directed (DD) algorithm. This then yields a semi-blind DFE with high speed and good convergence. Keywords—Adaptive Decision Feedback Equalizer, Performance Analysis, Finite Alphabet Case, Ill-Convergence, Convergence speed.
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