Machine Learning for Mitigation of Nonlinear Intersymbol Interference in Digital Coherent Optical Communication Systems - Dantas, Lucas C. [UNESP]; Cossa, Grazielle C. [UNESP]; Penchel, Rafael A. [UNESP]; De Oliveira, Jose Augusto [UNESP]; Abbade, Marcelo L. F. [UNESP]; De Abreu, Leandra I. [UNESP]; Garcia, Marlon R. [UNESP]; Guillardi, Hildo [UNESP]; Aldaya, Ivan [UNESP] (Institute of Electrical and Electronics Engineers (IEEE), 2024)
This paper explores the interaction between dispersion-induced intersymbol interference and self-phase modulation in coherent optical communication systems using raised cosine pulse shaping. In order to address this interaction, we trained a multilayer perceptron with adjacent symbols, demonstrating that utilizing information from multiple symbols enhances the system's ability to compensate for nonlinear distortion.
Keywords: Digital coherent optical communications; machine learning; nonlinear distortion