深度学习回归与SMF和FMF链接中QoT估计的分类

2022 Italian Conference on Optics and Photonics (ICOP) Pub Date : 2022-06-15 DOI:10.1109/ICOP56156.2022.9911716

M. A. Amirabadi, M. Kahaei, S. Nezamalhosseini, A. Carena

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引用次数: 2

摘要

我们研究了基于深度学习的回归和分类，用于单模和少模光纤链路的传输质量估计。结果表明，两种方法均具有较好的效率和较低的复杂度，但回归性能更好，分类速度更快。

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Deep Learning Regression vs. Classification for QoT Estimation in SMF and FMF Links

We investigate deep learning-based regression and classification for quality of transmission estimation in single-mode and few-mode fiber links. Results show efficiency and low complexity in both methods, however, regression performs better and classification is faster.

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2022 Italian Conference on Optics and Photonics (ICOP)

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