Machine-learning-based Coherent Optical Communication System

Wei Chen; Junfeng Zhang; Mingyi Gao; Yang Ye; Xiaoyi Chen; Bowen Chen

doi:10.1364/ACPC.2017.M3G.6

Asia Communications and Photonics Conference
OSA Technical Digest (online) (Optica Publishing Group, 2017),
paper M3G.6
•https://doi.org/10.1364/ACPC.2017.M3G.6

Machine-learning-based Coherent Optical Communication System

Wei Chen, Junfeng Zhang, Mingyi Gao, Yang Ye, Xiaoyi Chen, and Bowen Chen

Asia Communications and Photonics Conference 2017

Guangzhou, Guangdong China
10–13 November 2017
ISBN: 978-1-943580-34-7

From the session
Transmission Techniques II (M3G)

Not Accessible

Your library or personal account may give you access

Get PDF
Email
Share
Get Citation
Copy Citation Text
W. Chen, J. Zhang, M. Gao, Y. Ye, X. Chen, and B. Chen, "Machine-learning-based Coherent Optical Communication System," in Asia Communications and Photonics Conference, OSA Technical Digest (online) (Optica Publishing Group, 2017), paper M3G.6.

Export Citation
- BibTex
- Endnote (RIS)
- HTML
- Plain Text
Citation alert
Save article

Abstract

We experimentally demonstrate a 75-Gb/s 64-QAM coherent optical communication system using support-vector machine (SVM) decision boundary algorithm to create the optimal symbol decision boundary for improving the system performance.

PDF Article

More Like This

Machine Learning Methods for Optical Communication Systems

Faisal Nadeem Khan, Chao Lu, and Alan Pak Tao Lau
SpW2F.3 Signal Processing in Photonic Communications (SPPCom) 2017

Nonlinear Inter-Subcarrier Intermixing Reduction in Coherent Optical OFDM using Fast Machine Learning Equalization

Elias Giacoumidis, Jinlong Wei, Sofien Mhatli, Marc F. C. Stephens, Nick J. Doran, Andrew D. Ellis, and Benjamin J. Eggleton
W3J.2 Optical Fiber Communication Conference (OFC) 2017

Machine learning concepts in coherent optical communication systems

Darko Zibar and Christian Schäffer
ST2D.1 Signal Processing in Photonic Communications (SPPCom) 2014

Previous Article Next Article