Invention Grant
- Patent Title: G-OSNR estimation on dynamic PS-QAM channels using hybrid neural networks
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Application No.: US16596582Application Date: 2019-10-08
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Publication No.: US10887009B2Publication Date: 2021-01-05
- Inventor: Yue-Kai Huang , Shaoliang Zhang , Ezra Ip , Jiakai Yu
- Applicant: NEC Laboratories America, Inc.
- Applicant Address: US NJ Princeton
- Assignee: NEC Laboratories America, Inc.
- Current Assignee: NEC Laboratories America, Inc.
- Current Assignee Address: US NJ Princeton
- Agent Joseph Kolodka
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/04 ; H04L27/34 ; H04B10/07 ; H04B10/079

Abstract:
Aspects of the present disclosure describe systems, methods and structures in which a hybrid neural network combining a CNN and several ANNs are shown useful for predicting G-ONSR for Ps-256QAM raw data in deployed SSMF metro networks with 0.27 dB RMSE. As demonstrated, the CNN classifier is trained with 80.96% testing accuracy to identify channel shaping factor. Several ANN regression models are trained to estimate G-OSNR with 0.2 dB for channels with various constellation shaping.
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