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...

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Vydané v:	Journal of lightwave technology Ročník 36; číslo 20; s. 4843 - 4855
Hlavní autori:	Karanov, Boris, Chagnon, Mathieu, Thouin, Felix, Eriksson, Tobias A., Bulow, Henning, Lavery, Domanic, Bayvel, Polina, Schmalen, Laurent
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 15.10.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	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
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