Machine learning for QoT estimation of unseen optical network states

T Panayiotou, G Savva, B Shariati, I Tomkos… - Optical Fiber …, 2019 - opg.optica.org
Machine Learning for QoT Estimation of Unseen Optical Network States Page 1 Tu2E.2.pdf OFC
2019 © OSA 2019 Machine Learning for QoT Estimation of Unseen Optical Network States Tania …

Learning quantile QoT models to address uncertainty over unseen lightpaths

H Maryam, T Panayiotou, G Ellinas - Computer Networks, 2022 - Elsevier
Uncertainty in quality-of-transmission (QoT) estimation is traditionally addressed through
empirical, myopic margins, ignoring the fact that each unseen lightpath is subject to different …

Dynamic impairment-aware RMCSA in multi-core fiber-based elastic optical networks

J Su, J Zhang, J Wang, D Ren, J Hu, J Zhao - Optics Communications, 2022 - Elsevier
Abstract Space division multiplex elastic optical networks (SDM-EONs) based on multi-core
fiber (MCF) have been regarded as one of the promising solutions to address the future …

Shared backup path protection-based resource allocation considering inter-core and inter-mode crosstalk for spectrally-spatially elastic optical networks

J Halder, M Maity, E Oki… - IEEE Communications …, 2021 - ieeexplore.ieee.org
In the future, the most challenging issue for network operators will be to provide survivability
against failure and enhance resource utilization simultaneously in spectrally-spatially elastic …

Ultra-wideband WDM optical network optimization

S Kozdrowski, M Żotkiewicz, S Sujecki - Photonics, 2020 - mdpi.com
Ultra-wideband wavelength division multiplexed networks enable operators to use more
effectively the bandwidth offered by a single fiber pair and thus make significant savings …

Deep neural network-based QoT estimation for SMF and FMF links

MA Amirabadi, MH Kahaei… - Journal of Lightwave …, 2022 - ieeexplore.ieee.org
Quality of transmission (QoT) estimation tools for fiber links are the enabler for the
deployment of reconfigurable optical networks. To dynamically set up lightpaths based on …

Deep Learning-Based Classification for QoT Estimation in SMF and FMF Links

MA Amirabadi, SA Nezamalhosseini… - Journal of Lightwave …, 2024 - ieeexplore.ieee.org
Prediction of the quality of transmission (QoT) in optical communication networks is a critical
task to ensure reliable transmission and optimized operation. Accurate QoT estimation is …

QoT-aware performance evaluation of spectrally–spatially flexible optical networks over FM-MCFs

F Arpanaei, N Ardalani, H Beyranvand… - Journal of Optical …, 2020 - ieeexplore.ieee.org
In this paper, we study the quality of transmission (QoT) aware routing, modulation level, and
resource assignment problem for transparent flexible optical networks over few-mode multi …

Machine learning assisted optimization of dynamic crosstalk-aware spectrally-spatially flexible optical networks

M Klinkowski, P Ksieniewicz, M Jaworski… - Journal of Lightwave …, 2020 - ieeexplore.ieee.org
We focus on optimization of dynamic spectrally-spatially flexible optical networks (SS-FONs),
in which distance-adaptive, spectral super-channel (SCh) transmission is realized over …

Modeling optical fiber space division multiplexed quantum key distribution systems

M Ureña, I Gasulla, FJ Fraile, J Capmany - Optics express, 2019 - opg.optica.org
We report a model to use to evaluate the performance of multiple quantum key distribution
(QKD) channel transmission using spatial division multiplexing (SDM) in multicore (MCF) …