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

Zhili Zhou | Zendy; Yiju Zhan | Zendy; Qingling Cai | Zendy; Xiukai Ruan | Zendy; Guihua Cui | Zendy; Yuxing Dai | Zendy; Haiyong Zhu | Zendy

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

Author(s) -

Zhili Zhou,

Yiju Zhan,

Qingling Cai,

Xiukai Ruan,

Guihua Cui,

Yuxing Dai,

Haiyong Zhu

Publication year - 2017

Publication title -

ieee photonics journal

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.725

H-Index - 73

eISSN - 1943-0655

pISSN - 1943-0647

DOI - 10.1109/jphot.2017.2754504

Subject(s) - engineered materials, dielectrics and plasmas , photonics and electrooptics

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

$\alpha$

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.

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