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  4. Maximizing Fiber Cable Capacity Under A Supply Power Constraint Using Deep Neural Networks
 
conference paper

Maximizing Fiber Cable Capacity Under A Supply Power Constraint Using Deep Neural Networks

Cho, Junho
•
Chandrasekhar, Sethumadhavan
•
Sula, Erixhen  
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January 1, 2020
2020 Optical Fiber Communications Conference And Exposition (Ofc)
Optical Fiber Communications Conference and Exposition (OFC)

We experimentally achieve a 19% capacity gain per Watt of electrical supply power in a 12-span link by eliminating gain flattening filters and optimizing launch powers using deep neural networks in a parallel fiber context. (C) 2020 The Authors

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Type
conference paper
DOI
10.1364/OFC.2020.W1K.2
Web of Science ID

WOS:000676346200173

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

2020-01-01

Publisher

IEEE

Publisher place

New York

Published in
2020 Optical Fiber Communications Conference And Exposition (Ofc)
ISBN of the book

978-1-9435-8071-2

Subjects

Engineering, Electrical & Electronic

•

Telecommunications

•

Engineering

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LINX  
Event nameEvent placeEvent date
Optical Fiber Communications Conference and Exposition (OFC)

San Diego, CA

Mar 08-12, 2020

Available on Infoscience
August 28, 2021
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/180988
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