Applications of expectation maximization algorithm for coherent optical communication

L. Carvalho (Invited author), J. Oliveira (Invited author), Darko Zibar (Invited author), O. Winther (Invited author), Robert Borkowski (Invited author), Idelfonso Tafur Monroy (Invited author)

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    In this invited paper, we present powerful statistical signal processing methods, used by machine learning community, and link them to current problems in optical communication. In particular, we will look into iterative maximum likelihood parameter estimation based on expectation maximization algorithm and its application in coherent optical communication systems for linear and nonlinear impairment mitigation. Furthermore, the estimated parameters are used to build the probabilistic model of the system for the synthetic impairment generation.
    Original languageEnglish
    Title of host publicationProceedings of the 22nd European Signal Processing Conference (EUSIPCO)
    Publication date2014
    ISBN (Print)9780992862619
    Publication statusPublished - 2014
    SeriesProceedings of the European Signal Processing Conference


    • Signal Processing and Analysis
    • Abstracts
    • Communities
    • expectation maximization
    • machine learning
    • nonlinear impairments
    • optical communication
    • Optical modulation
    • Optical polarization
    • Optical sensors


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