Information Entropy and Fuzzy Logic Based Equalizer for PolMux QAM Coherent Optical Communication Systems

In polarization-multiplexed (PolMux) coherent optical communication systems, adaptive blind equalizer is efficient in demultiplexing and mitigating intersymbol interference (ISI). A novel blind algorithm based on Information Entropy and fuzzy logic is proposed, in which the Renyi's <inline-f...

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Bibliographic Details
Published inIEEE photonics journal Vol. 9; no. 5; pp. 1 - 16
Main Authors Zhou, Zhili, Zhan, Yiju, Cai, Qingling, Ruan, Xiukai, Cui, Guihua, Dai, Yuxing, Zhu, Haiyong
Format Journal Article
LanguageEnglish
Published IEEE 01.10.2017
Subjects
Cost function
Entropy
equalizer
Equalizers
Fuzzy logic
Information entropy
Kernel
optical communication
Optical fiber communication
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Summary:In polarization-multiplexed (PolMux) coherent optical communication systems, adaptive blind equalizer is efficient in demultiplexing and mitigating intersymbol interference (ISI). A novel blind algorithm based on Information Entropy and fuzzy logic is proposed, in which the Renyi's <inline-formula><tex-math notation="LaTeX">\alpha</tex-math> </inline-formula> entropy is adopted to measure the uncertainty of error between the desired and estimated probability density function (PDF). The nonparametric PDF estimator of Parzen window method is employed to estimate the PDF of symbols. Meantime, a fuzzy-logic tuning unit is designed to adjust the kernel size of Parzen window, which leads to fast convergence rate and small steady mean-square error. By simulation in PolMux-16 quadrature amplitude modulation (QAM) coherent systems, the correctness and effectiveness of the proposed algorithm are verified.
ISSN:1943-0655
1943-0647
DOI:10.1109/JPHOT.2017.2754504