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Complex-Channel Blind Equalization Using Cross-Correntropy (상호 코렌트로피를 이용한 복소 채널 블라인드 등화)

  • Kim, Nam-Yong
    • Journal of Internet Computing and Services
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    • v.11 no.5
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    • pp.19-26
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    • 2010
  • The criterionmaximizing cross-correntropy (MCC) of two different random variables has yielded superior performance comparing to mean squared error criterion. In this paper we present a complex-valued blind equalizer algorithm for QAM and complex channel environments based on cross-correntropy criterion which uses, as two variables, equalizer output PDF and Parzen PDF estimate of a self-generated symbol set. Simulation results show significantly enhanced performance of symbol-point concentration with no phase rotation in complex-channel communication.

Euclidian Distance Minimization of Probability Density Functions for Blind Equalization

  • Kim, Nam-Yong
    • Journal of Communications and Networks
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    • v.12 no.5
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    • pp.399-405
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    • 2010
  • Blind equalization techniques have been used in broadcast and multipoint communications. In this paper, two criteria of minimizing Euclidian distance between two probability density functions (PDFs) for adaptive blind equalizers are presented. For PDF calculation, Parzen window estimator is used. One criterion is to use a set of randomly generated desired symbols at the receiver so that PDF of the generated symbols matches that of the transmitted symbols. The second method is to use a set of Dirac delta functions in place of the PDF of the transmitted symbols. From the simulation results, the proposed methods significantly outperform the constant modulus algorithm in multipath channel environments.

Blind Equalization based on Maximum Cross-Correntropy Criterion using a Set of Randomly Generated Symbol (랜덤 심볼을 사용한 최대 코렌트로피 기준의 블라인드 등화)

  • Kim, Nam-Yong;Kang, Sung-Jin;Hong, Dae-Ki
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.1C
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    • pp.33-39
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    • 2010
  • Correntropy is a generalized correlation function that contains higher order moments of the probability density function (PDF) than the conventional moment expansions. The criterion maximizing cross-correntropy (MCC) of two different random variables has yielded superior performance particularly in nonlinear, non-Gaussian signal processing comparing to mean squared error criterion. In this paper we propose a new blind equalization algorithm based on cross-correntropy criterion which uses, as two variables, equalizer output PDF and Parzen PDF estimate of a set of randomly generated symbols that complies with the transmitted symbol PDF. The performance of the proposed algorithm based on MCC is compared with the Euclidian distance minimization.

A New Criterion of Information Theoretic Optimization and Application to Blind Channel Equalization (새로운 정보이론적 최적기준에 의한 블라인드 등화)

  • Kim, Nam-Yong;Yang, Liuqing
    • Journal of Internet Computing and Services
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    • v.10 no.1
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    • pp.11-17
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    • 2009
  • Blind equalization techniques have been used in multipoint communication on which the research on the internet has focused. In this paper, a criterion of minimizing Euclidian Distance between two PDFs for adaptive blind equalizers has been presented. In order for ED expressed with Parzen PDFs to be minimized, we propose to use a set of randomly generated desired symbols at the receiver so that the PDF of the generated symbols matches that of the transmitted symbols. From the simulation results, the proposed method has shown superior error performance even in severe channel environments in which CMA has shown severe performance degradation. This indicates that the proposed algorithm can be considered relatively insensitive to ESR variations compared to CMA. As a field of ITL, ED minimization using Parzen PDFs has shown possibilities of being successfully applied to blind equalization.

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