OSNR monitoring based on a low-bandwidth coherent receiver and LSTM classifier
Robustness
DOI:
10.1364/oe.412079
Publication Date:
2020-12-22T12:30:08Z
AUTHORS (8)
ABSTRACT
Optical signal-to-noise ratio (OSNR) monitoring is one of the core tasks advanced optical performance (OPM) technology, which plays an essential role in future intelligent communication networks. In contrast to many regression-based methods, we convert continuous OSNR into a classification problem by restricting outputs neural network-based classifier discrete intervals. We also use low-bandwidth coherent receiver for obtaining time domain samples and long short-term memory (LSTM) network as chromatic dispersion-resistant classifier. The proposed scheme cost efficient compatible with our previously multi-purpose OPM platform. Both simulation experimental verification show that technique achieves high accuracy robustness low computational complexity.
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