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Communication Dans Un Congrès Année : 2016

A machine learning approach for dynamic optical channel add/drop strategies that minimize EDFA power excursions

Résumé

We demonstrate a machine learning approach to characterize channel dependence of power excursions in multi-span EDFA networks. This technique can determine accurate recommendations for channel add/drop with minimal excursions and is applicable to different network designs
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Dates et versions

hal-01434025 , version 1 (13-01-2017)

Identifiants

  • HAL Id : hal-01434025 , version 1

Citer

Yishen Huang, Wiem Samoud, Craig L. Gutterman, Cédric Ware, Mounia Lourdiane, et al.. A machine learning approach for dynamic optical channel add/drop strategies that minimize EDFA power excursions. ECOC 2016 : 42nd European Conference on Optical Communication, Sep 2016, Düsseldorf, Germany. pp.268 - 270. ⟨hal-01434025⟩
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