@inproceedings{5cac974cc722428585be79b81990818e,
title = "Perturbative Machine Learning Technique for Nonlinear Impairments Compensation in WDM Systems",
abstract = "We propose a perturbation-based receiver-side machine-learning equalizer for inter- and intra-channel nonlinearity compensation in WDM systems. We show 1.6 dB and 0.6 dB Q2 -factor improvement compared with linear equalization and DBP respectively for 1000km transmission of 3×128Gbit/s DP-16QAM signal.",
author = "Evgeny Averyanov and Redyuk, {Alexey A.} and Oleg Sidelnikov and Mariia Sorokina and Fedoruk, {Mikhail P.} and Turitsyn, {Sergei K.}",
note = "{\textcopyright} 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.",
year = "2018",
month = nov,
day = "15",
doi = "10.1109/ECOC.2018.8535338",
language = "English",
isbn = "978-1-5386-4863-6",
booktitle = "2018 European Conference on Optical Communication (ECOC)",
publisher = "IEEE",
address = "United States",
}