End-to-End Learning in Optical Fiber Communications: Experimental Demonstration and Future Trends

被引：8

作者：

Karanov, Boris ^{[1
,2
,3
]}

Oliari, Vinicius ^{[2
]}

Chagnon, Mathieu ^{[3
]}

Liga, Gabriele ^{[2
]}

Alvarado, Alex ^{[2
]}

Aref, Vahid ^{[3
]}

Lavery, Domanic ^{[1
]}

Bayvel, Polina ^{[1
]}

Schmalen, Laurent ^{[4
]}

机构：

[1] UCL, Dept Elect & Elect Engn, Opt Networks Grp, London WC1E 7JE, England

[2] Eindhoven Univ Technol, NL-5600 MB Eindhoven, Netherlands

[3] Nokia Bell Labs, D-70435 Stuttgart, Germany

[4] Karlsruhe Inst Technol, Commun Engn Lab, D-76131 Karlsruhe, Germany

来源：

2020 EUROPEAN CONFERENCE ON OPTICAL COMMUNICATIONS (ECOC) | 2020年

基金：

欧洲研究理事会; 欧盟地平线“2020”; 英国工程与自然科学研究理事会;

关键词：

D O I：

10.1109/ECOC48923.2020.9333265

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Fiber-optic auto-encoders are demonstrated on an intensity modulation/direct detection test-bed, outperforming state-of-the-art signal processing. Algorithms for end-to-end optimization using experimentally collected data are discussed. The end-to-end learning framework is extended for performing optimization of the symbol distribution in probabilistically-shaped coherent systems.

引用

页数：4

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