Decision Feedback Blind Equalizer with Tap-Leaky Whitening for Stable Structure-Criterion Switching

Abstract

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 decisiondirected 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.

Maximum entropy whitening algorithm with adaptive neuron slope for blind DFE

“…Finally, the SFBF switches itself into the classical decision feedback equalizer performing DD-LMS adaptation (tracking mode). The phase rotator PR is active from the early beginning of equalization, and it is implemented by the classical phase locked loop [1] including some modifications [7].…”

“…In [6] and [7] it is evidenced that the optimal value of the slope D  depends only on the given signal constellation, and the optimal slope D  can be seen as a statistical constant of the given signal and neuron function. On the other hand, the selection of the slope W  is a more complex problem.…”

“…Later in [6] and [7], the SO-DFE scheme was innovated by the soft FBF (SFBF) equalizer which was introduced instead of the original MMSE-FBF filter to improve the estimation of a severe channel spectrum and to mitigate effects of a sudden equalizer structure-criterion switching. In this innovated SO-DFE scheme, named Soft-DFE, the SFBF equalizer exploits the information-theoretic blind deconvolution approach by Bell and Sejnowski [8] and, specifically, the equivalence between the minimization of mutual information between interfering symbols and the maximization of the joint Shannon's entropy of equalizer outputs.…”

“…In this innovated SO-DFE scheme, named Soft-DFE, the SFBF equalizer exploits the information-theoretic blind deconvolution approach by Bell and Sejnowski [8] and, specifically, the equivalence between the minimization of mutual information between interfering symbols and the maximization of the joint Shannon's entropy of equalizer outputs. It was verified by simulations that the Soft-DFE, employing the Joint Entropy Maximization (JEM) cost [9], attains remarkably better MSE convergence than the original SO-DFE in the system transmitting m-QAM (quadrature amplitude modulation), m=16,32,64, signals over deep-fade channels [6], [7].…”

“…Although very attractive, it has been noticed in [10] and later confirmed in [7] that the practical self-optimized DFE scheme, employing finite length filters, presents some limitations which are manifested as follows. The Soft-DFE deals with the position changing of the SFBF filter during the equalizer convergence process (see Fig.…”