• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.5
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• pp.237-243
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• 2014

In this paper, a calculation-efficient method for weight update in the algorithm based on maximization of the zero-error probability (MZEP) is proposed. This method is to utilize the current slope value in calculation of the next slope value, replacing the block processing that requires a summation operation in a sample time period. The simulation results shows that the proposed method yields the same performance as the original MZEP algorithm while significantly reducing the computational time and complexity with no need for a buffer for error samples. Also the proposed algorithm produces faster convergence speed than the algorithm that is based on the error-entropy minimization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12C
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• pp.753-758
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• 2011

The constant modulus algorithm (CMA) widely used in blind equalization applications minimizes the averaged power of constant modulus error (CME) defined as the difference between an instant output power and a constant modulus. In this paper, a decision feedback version of the linear blind algorithm based on maximization of the zero-error probability for CME is proposed. The Gaussian kernel of the maximum zero-error criterion is analyzed to have the property to cut out excessive CMEs that may be induced from severely distorted channel characteristics. Decision feedback approach to the maximum zero-error criterion for CME is developed based on the characteristic that the Gaussian kernel suppresses the outliers and this prevents error propagation to some extent. Compared to the linear algorithm based on maximum zero-error probability for CME in the simulation of blind equalization environments, the proposed decision feedback version has superior performance enhancement particularly in cases of severe channel distortions.

• Journal of Communications and Networks
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• v.12 no.5
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• pp.459-465
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• 2010

A new blind equalization algorithm that is based on maximizing the probability that the constant modulus errors concentrate near zero is proposed. The cost function of the proposed algorithm is to maximize the probability that the equalizer output power is equal to the constant modulus of the transmitted symbols. Two blind information-theoretic learning (ITL) algorithms based on constant modulus error signals are also introduced: One for minimizing the Euclidean probability density function distance and the other for minimizing the constant modulus error entropy. The relations between the algorithms and their characteristics are investigated, and their performance is compared and analyzed through simulations in multi-path channel environments. The proposed algorithm has a lower computational complexity and a faster convergence speed than the other ITL algorithms that are based on a constant modulus error. The error samples of the proposed blind algorithm exhibit more concentrated density functions and superior error rate performance in severe multi-path channel environments when compared with the other algorithms.

• Journal of Internet Computing and Services
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• v.11 no.5
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• pp.1-8
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• 2010

This paper presentsthe performance study of blind equalizer algorithms for impulsive-noise environments based on Gaussian kernel and constant modulus error(CME). Constant modulus algorithm(CMA) based on CME and mean squared error(MSE) criterion fails in impulsive noise environment. Correntropy blind method recently introduced for impulsive-noise resistance has shown in PAM system not very satisfying results. It is revealed in theoretical and simulation analysis that the maximization of zero-error probability based on CME(MZEP-CME) originally proposed for Gaussian noise environments produces superior performance in impulsive noise channels as well. Gaussian kernel of MZEP-CME has a strong effect of becoming insensitive to the large differences between the power of impulse-infected outputs and the constant modulus value.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8C
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• pp.516-521
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• 2011

In this paper, a nonlinear algorithm that maximizes zero-error probability (MZEP) with decision feedback (DF) is proposed to counteract both of severely distorted multi-path fading effect and impulsive noise. The proposed MZEP-DF algorithm has shown the immunity to impulsive noise and the ability of the feedback filter section to cancel the remaining intersymbol interference as well. Compared with the linear MZEP algorithm, it yields above 10 dB enhancement of steady state MSE performance in severely distorted multipath fading channels with impulse noise where the least mean square (LMS) algorithm does not converge below -3dB of MSE.