Optimizing Gain Shaping Filters with Neural Networks for Maximum Cable Capacity under Electrical Power Constraints
Cho, Junho; Raybon, Greg; Burrows, Ellsworth; Antona, Jean-Christophe; Fontaine, Nicolas; Ryf, Roland; Chen, Haoshuo; Chandrasekhar, Sethumadhavan; Sula, Erixhen; Olsson, Samuel; Grubb, Steve; Winzer, Peter
2021

Abstract

We experimentally demonstrate capacity gains of up to 23% under electrical supply power constraints in a long-haul optical fiber cable by optimizing the gain shaping filters using neural networks.

Details

Title Optimizing Gain Shaping Filters with Neural Networks for Maximum Cable Capacity under Electrical Power Constraints
Author(s) Cho, Junho ; Raybon, Greg ; Burrows, Ellsworth ; Antona, Jean-Christophe ; Fontaine, Nicolas ; Ryf, Roland ; Chen, Haoshuo ; Chandrasekhar, Sethumadhavan ; Sula, Erixhen ; Olsson, Samuel ; Grubb, Steve ; Winzer, Peter
Published in 2020 European Conference On Optical Communications (Ecoc)
Conference European Conference on Optical Communications (ECOC), Dec 06-10, 2020, ELECTR NETWORK
Date 2021-01-01
Publisher New York, IEEE
ISBN 978-1-7281-7361-0
DOI https://doi.org/10.1109/ECOC48923.2020.9333383
Other identifier(s) View record in Web of Science
Laboratories LINX
Record Appears in Scientific production and competences > I&C - School of Computer and Communication Sciences > IINFCOM > LINX - Laboratory for Information in Networked Systems
Peer-reviewed publications
Conference Papers
Work produced at EPFL
Published
Record creation date 2021-07-31