The research presented in this paper improves the structure-criterion switching performance of the blind decision feedback equalizer (DFE) which eliminates error propagation effects by optimizing both the structure and the cost criterion. To conquer the complexity of the 64-QAM (quadrature amplitude modulated) signal constellation, the stochastic entropy-gradient algorithm is additionally regularized by the coefficient leaky term to avoid a coefficients norm overgrowth of the received signal whitener. Effectively, the leak of coefficients is employed to ensure a stable structure-criterion switching of DFE between blind and decision-directed operation modes. The optimization of the resulting whitening algorithm is achieved by means of two free, leaky and entropic, parameters which act in opposition to each other. Both, the influence of the 64-QAM signal on the feedback filter behavior and the parametric optimization of the whitening algorithm are analyzed through simulations. 1. Introduction Blind equalization methods are introduced as an alternative approach to the data communication concept employing a specially designed training sequence (pilot) to direct the train of receiver adaptive parameters [1, 2]. By using blind adaptive equalizers, which work without the assistance of a pilot, it is possible to increase effective system data rates and, also, to realize system applications where the train with a pilot is not possible [3, 4]. Unlike a linear equalizer which strives to complete an inverse channel response by a finite impulse response filter, a decision feedback equalizer (DFE) divides equalization task between linear feedforward and nonlinear feedback filters (equalizers). In such a manner, according to the hypothesis of correctly detected symbols, DFE exploits a nonlinear discrete nature of transmitted symbols to eliminate postcursor intersymbol interference (ISI) without a noise enhancement [5] using a relatively small number of coefficients [6]. This property of DFE is particularly important in systems characterized by deep spectral nulls channels. On the other hand, the main drawback of a DFE is error propagation phenomena which generally degrades its performance and can lead to an equalization failure depending on the length of error packets. For a blind DFE, the error propagation becomes a particularly critical issue because it appears inherently at the starting phase of equalization. Therefore, blind DFEs appeal for more efficient algorithms and signal processing techniques than their nonblind counterparts [7–13]. Motivated by the works of
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