N Guo, L Li, B Mukherjee… - Journal of Optical …, 2022 - ieeexplore.ieee.org
Machine learning (ML)-based methods are being widely explored to predict the quality of transmission (QoT) of a lightpath. They are expected to reduce the signal-to-noise ratio …
Failures in the optical layer might impact the quality of supported services. We experimentally characterize several failure causes and propose an effective machine …
In elastic optical networks (EONs), effective soft failure localization is of paramount importance to early detection of service level agreement violations while anticipating …
J Babbar, A Triki, R Ayassi, M Laye - Journal of Optical …, 2022 - opg.optica.org
The increase in computing capacity and the huge amount of available data have significantly accelerated the use of artificial intelligence and machine learning algorithms to …
X Liu, H Lun, M Fu, Y Fan, L Yi, W Hu, Q Zhuge - Applied Sciences, 2020 - mdpi.com
With the development of 5G technology, high definition video and internet of things, the capacity demand for optical networks has been increasing dramatically. To fulfill the capacity …
E Seve, J Pesic, Y Pointurier - 2020 International Conference …, 2020 - ieeexplore.ieee.org
Using machine learning and Signal-to-Noise Ratio (SNR) monitoring, we reduce uncertainties on output power profile and noise figure (NF) of each EDFA in an optical …
Predicting the quality of transmission (QoT) of a lightpath prior to its deployment is a step of capital importance for an optimized design of optical networks. Due to the continuous …