End-to-End Deep Learning of Optical Fiber Communications

In this paper, we implement an optical fiber communication system as an end-to-end deep neural network, including the complete chain of transmitter, channel model, and receiver. This approach enables the optimization of the transceiver in a single end-to-end process. We illustrate the benefits of th...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Journal of lightwave technology Jg. 36; H. 20; S. 4843 - 4855
Hauptverfasser:	Karanov, Boris, Chagnon, Mathieu, Thouin, Felix, Eriksson, Tobias A., Bulow, Henning, Lavery, Domanic, Bayvel, Polina, Schmalen, Laurent
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 15.10.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial neural networks Communication systems Communications systems Computer networks Computer simulation Deep learning detection Equalization Error correction Machine learning modulation neural networks Optical communication optical fiber communication Optical fibers Optical transmitters Optimization Pulse amplitude modulation Receivers Reconfiguration Training Transceivers Transmitters
ISSN:	0733-8724, 1558-2213
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!