利用机器学习估计现网中的传输质量
网络与互联网体系结构
2021-12-09 v1
摘要
我们展示了利用在大参数空间合成数据上训练的神经网络，在现网中进行传输质量（QoT）估计。该机器学习模型在广泛的配置范围内，预测的光通路性能信噪比误差小于0.5dB。
引用
@article{arxiv.2112.04031,
title = {Estimating Quality of Transmission in a Live Production Network using Machine Learning},
author = {Jasper Müller and Tobias Fehenberger and Sai Kireet Patri and Kaida Kaeval and Helmut Griesser and Marko Tikas and Jörg-Peter Elbers},
journal= {arXiv preprint arXiv:2112.04031},
year = {2021}
}
备注
The work has been partially funded by the German Ministry of Education and Research in the project OptiCON (contract #16KIS0989K)