Sparse Identification for Nonlinear Optical communication systems

Sorokina, Mariia, Sygletos, Stylianos and Turitsyn, Sergei (2017). Sparse Identification for Nonlinear Optical communication systems. IN: ICTON 2017 - 19th International Conference on Transparent Optical Networks. ESP: IEEE.

Abstract

We have developed a low complexity machine learning based nonlinear impairment equalization scheme and demonstrated its successful performance in SDM transmission links achieving compensation of both inter- and intra- channel Kerr-based nonlinear effects. The method operates in one sample per symbol and in one computational step. It is adaptive, i.e. it does not require a knowledge of system parameters, and it is scalable to different power levels and modulation formats. The method can be straightforwardly expanded to multi-channel systems and to any other type of nonlinear impairment.

Publication DOI: https://doi.org/10.1109/ICTON.2017.8024969
Divisions: Engineering & Applied Sciences
Engineering & Applied Sciences > Aston Institute of Photonics Technology
Engineering & Applied Sciences > Electrical, Electronic & Power Engineering
Engineering & Applied Sciences > Systems analytics research institute (SARI)
Additional Information: © Copyright 2017 IEEE - All rights reserved Funding: EPSRC project UNLOC EP/J017582/1 and EU-FP7 INSPACE project under grant agreement N.619732
Event Title: 19th International Conference on Transparent Optical Networks, ICTON 2017
Event Type: Other
Event Dates: 2017-07-02 - 2017-07-06
Uncontrolled Keywords: fiber optic communications,machine learning,nonlinear analysis,spatial division multiplexing,Computer Networks and Communications,Electrical and Electronic Engineering,Electronic, Optical and Magnetic Materials
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
Published Date: 2017-09-04
Authors: Sorokina, Mariia
Sygletos, Stylianos ( 0000-0003-2063-8733)
Turitsyn, Sergei ( 0000-0003-0101-3834)

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