Multi-Objective Optimization of Machine Learning-Based Nonlinear Equalizers for Digital Coherent Optical Interconnects

Multi-Objective Optimization of Machine Learning-Based Nonlinear Equalizers for Digital Coherent Optical Interconnects

The growing demand for high-capacity optical networks has driven the advancement of digital coherent optical communication systems, which rely on sophisticated signal processing to mitigate transmission impairments, including nonlinear fiber distortions. Traditional nonlinear compensation techniques...

Full description

Saved in:
Bibliographic Details
Main Authors: Lucas C. Dantas, Hildo Guillardi Junior, Plinio Dester, Rafael A. Penchel, Jose Augusto de Oliveira, Marcelo L. F. Abbade, Leandra I. Abreu, Jinlong Wei, Ivan Aldaya
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Digital coherent optical communication systems
nonlinear distortion
equalizer
Online Access:https://ieeexplore.ieee.org/document/11078271/
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://ieeexplore.ieee.org/document/11078271/

Similar Items