Machine Learning for Optical Performance Monitoring from Directly Detected PDM-QAM Signals
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:
Wass, Jesper; Thrane, Jakob; Piels, Molly; Diniz, Julio C. M.; Jones, Rasmus; Zibar, Darko (DTU Fotonik, Technical University of Denmark, Build. 343, 2800, Denmark)
Abstract:
Supervised machine learning methods are applied and demonstrated experimentally for inband OSNR estimation and modulation format classification in optical communication systems. The proposed methods accurately evaluate coherent signals up to 64QAM using only intensity information.