Deep Learning Based OSNR Monitoring Independent of Modulation Format, Symbol Rate and Chromatic Dispersion
Conference: ECOC 2016 - 42nd European Conference on Optical Communication
09/18/2016 - 09/22/2016 at Düsseldorf, Deutschland
Proceedings: ECOC 2016
Pages: 3Language: englishTyp: PDF
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Authors:
Tanimura, Takahito (Fujitsu Laboratories Ltd., 4-1-1 Kamikodanaka, Nakahara-ku, Kawasaki 211-8588, Japan & Research Center for Advanced Science and Technology, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8904, Japan)
Hoshida, Takeshi; Kato, Tomoyuki; Watanabe, Shigeki; Rasmussen, Jens C. (Fujitsu Laboratories Ltd., 4-1-1 Kamikodanaka, Nakahara-ku, Kawasaki 211-8588, Japan)
Suzuki, Makoto; Morikawa, Hiroyuki (Research Center for Advanced Science and Technology, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8904, Japan)
Abstract:
A deep neural network (DNN) is employed for optical performance monitoring. We show that DNN-based monitor successfully estimates OSNR of signals modulated in different formats and symbol rates in the presence of chromatic dispersion and polarization rotation without prior knowledge.