Name
Abstract | ||
|---|---|---|
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 this method by applying it to intensity modulation/direct detection (IM/DD) systems and show that we c... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/JLT.2018.2865109 | Journal of Lightwave Technology |
Keywords | DocType | Volume |
Training,Machine learning,Receivers,Optical transmitters,Transceivers,Optimization,Communication systems | Journal | 36 |
Issue | ISSN | Citations |
20 | 0733-8724 | 17 |
PageRank | References | Authors |
1.36 | 9 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Boris Karanov | 1 | 18 | 2.07 |
| mathieu chagnon | 2 | 21 | 12.01 |
| F élix Thouin | 3 | 17 | 1.36 |
| tobias a eriksson | 4 | 29 | 9.21 |
| Henning Bülow | 5 | 40 | 12.02 |
| domanic lavery | 6 | 44 | 13.38 |
| Polina Bayvel | 7 | 94 | 28.01 |
| Schmalen, Laurent | 8 | 112 | 32.50 |