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arXiv · 1812.03792

Intelligent optical performance monitor using multi-task learning based artificial neural network

Zhiquan Wan·Zhenming Yu·Liang Shu·Yilun Zhao·Haojie Zhang·Kun Xu
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Abstract

An intelligent optical performance monitor using multi-task learning based artificial neural network (MTL-ANN) is designed for simultaneous OSNR monitoring and modulation format identification (MFI). Signals' amplitude histograms (AHs) after constant module algorithm are selected as the input features for MTL-ANN. The experimental results of 20-Gbaud NRZ-OOK, PAM4 and PAM8 signals demonstrate that MTL-ANN could achieve OSNR monitoring and MFI simultaneously with higher accuracy and stability compared with single-task learning based ANNs (STL-ANNs). The results show an MFI accuracy of 100% and OSNR monitoring root-mean-square error of 0.63 dB for the three modulation formats under consideration. Furthermore, the number of neuron needed for the single MTL-ANN is almost the half of STL-ANN, which enables reduced-complexity optical performance monitoring devices for real-time performance monitoring.

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Zhiquan Wan, Zhenming Yu, Liang Shu, Yilun Zhao, Haojie Zhang, Kun Xu. 2018-12-10. Intelligent optical performance monitor using multi-task learning based artificial neural network. https://doi.org/10.1364/oe.27.011281

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