Transfer Learning for BiLSTM-DNN-Based Optical Performance Monitoring in WDM Systems

We designed a more accurate and generalizable TL-based BiLSTM-DNN model for optical performance monitoring, using three-channel data reflecting inter-channel inference as the source domain, transferred to multi-channel WDM systems with flexible parameters.

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Publication Details

Published
2024-11-02
DOI
https://doi.org/10.1109/acp/ipoc63121.2024.10809778
Primary Topic
Optical Network Technologies
Type
article
Field-Weighted Citation Impact
0.00

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article

Transfer Learning for BiLSTM-DNN-Based Optical Performance Monitoring in WDM Systems

Yan Xue, Yameng Cao, Junyao Shi, Di Zhang
Optical Network Technologies
article

Transfer Learning for BiLSTM-DNN-Based Optical Performance Monitoring in WDM Systems

Yan Xue, Yameng Cao, Junyao Shi, Di Zhang
article en

Abstract

We designed a more accurate and generalizable TL-based BiLSTM-DNN model for optical performance monitoring, using three-channel data reflecting inter-channel inference as the source domain, transferred to multi-channel WDM systems with flexible parameters.

East China Normal University (CN)
National Natural Science Foundation of China, Science and Technology Commission of Shanghai Municipality, National Center of Competence in Research Quantum Science and Technology
Affordable and clean energy
Openalex Percentile: Top 77%
Optical Network Technologies
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