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  4. Optimizing Gain Shaping Filters with Neural Networks for Maximum Cable Capacity under Electrical Power Constraints
 
conference paper

Optimizing Gain Shaping Filters with Neural Networks for Maximum Cable Capacity under Electrical Power Constraints

Cho, Junho
•
Raybon, Greg
•
Burrows, Ellsworth
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January 1, 2021
2020 European Conference On Optical Communications (Ecoc)
European Conference on Optical Communications (ECOC)

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.

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Type
conference paper
DOI
10.1109/ECOC48923.2020.9333383
Web of Science ID

WOS:000662178500257

Author(s)
Cho, Junho
Raybon, Greg
Burrows, Ellsworth
Antona, Jean-Christophe
Fontaine, Nicolas
Ryf, Roland
Chen, Haoshuo
Chandrasekhar, Sethumadhavan
Sula, Erixhen  
Olsson, Samuel
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Date Issued

2021-01-01

Publisher

IEEE

Publisher place

New York

Published in
2020 European Conference On Optical Communications (Ecoc)
ISBN of the book

978-1-7281-7361-0

Subjects

Computer Science, Information Systems

•

Engineering, Electrical & Electronic

•

Optics

•

Telecommunications

•

Computer Science

•

Engineering

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LINX  
Event nameEvent placeEvent date
European Conference on Optical Communications (ECOC)

ELECTR NETWORK

Dec 06-10, 2020

Available on Infoscience
July 31, 2021
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/180330
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