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Conferences > Networks > 2022 > NeTh1C > NeTh1C.4

A Comprehensive Analysis on Machine Learning Based EDFA Gain Model

Yuli Chen, Xiaomin Liu, Yichen Liu, Yihao Zhang, Lilin Yi, Weisheng Hu, and Qunbi Zhuge

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Abstract

Five machine learning (ML) models are investigated for erbium-doped fiber amplifier (EDFA) gain modeling based on the experimental dataset. Result shows the modeling performance varies from model to model, providing useful information for practical utilization.

© 2022 The Author(s)

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