Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Nonlinear Interference Mitigation via Deep Neural Networks

Not Accessible

Your library or personal account may give you access

Abstract

A neural-network-based approach is presented to efficiently implement digital backpropagation (DBP). For a 32×100 km fiber-optic link, the resulting “learned” DBP significantly reduces the complexity compared to conventional DBP implementations.

© 2018 The Author(s)

PDF Article
More Like This
Deep Convolutional Recurrent Neural Network For Fiber Nonlinearity Compensation

Prasham Jain, Lutz Lampe, and Jeebak Mitra
We1C.5 European Conference and Exhibition on Optical Communication (ECOC) 2022

Few-bit Quantization of Neural Networks for Nonlinearity Mitigation in a Fiber Transmission Experiment

Jamal Darweesh, Nelson Costa, Antonio Napoli, Bernhard Spinnler, Yves Jaouën, and Mansoor Yousefi
We4C.4 European Conference and Exhibition on Optical Communication (ECOC) 2022

Towards FPGA Implementation of Neural Network-Based Nonlinearity Mitigation Equalizers in Coherent Optical Transmission Systems

Pedro J. Freire, Michael Anderson, Bernhard Spinnler, Thomas Bex, Jaroslaw E. Prilepsky, Tobias A. Eriksson, Nelson Costa, Wolfgang Schairer, Michaela Blott, Antonio Napoli, and Sergei K. Turitsyn
We1C.2 European Conference and Exhibition on Optical Communication (ECOC) 2022

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.