Neural-Network-Based G-OSNR Estimation of Probabilistic-Shaped 144QAM Channels in DWDM Metro Network Field Trial

Publication Date: 7/7/2019

Event: OECC/PSC 2019

Reference: TuA1-3: 1-4, 2019

Authors: Jiakai Yu, NEC Laboratories America, Inc., University of Arizona; Yue-Kai Huang, NEC Laboratories America, Inc.; Shaoliang Zhang, NEC Laboratories America, Inc.; Ezra Ip, NEC Laboratories America, Inc.; Daniel C. Kilper, University of Arizona; Tiejun J. Xia, Verizon; Glenn A. Wellbrock, Verizon

Abstract: A two-stage neural network model is applied on captured PS-144QAM raw data to estimate channel G-OSNR in a metro network field trial. We obtained 0.27dB RMSE with first-stage CNN classifier and second-stage ANN regressions.

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