An overview on application of machine learning techniques in optical networks
Today's telecommunication networks have become sources of enormous amounts of widely
heterogeneous data. This information can be retrieved from network traffic traces, network …
heterogeneous data. This information can be retrieved from network traffic traces, network …
[HTML][HTML] Artificial intelligence (AI) methods in optical networks: A comprehensive survey
Artificial intelligence (AI) is an extensive scientific discipline which enables computer
systems to solve problems by emulating complex biological processes such as learning …
systems to solve problems by emulating complex biological processes such as learning …
Machine learning for network automation: overview, architecture, and applications [Invited Tutorial]
Networks are complex interacting systems involving cloud operations, core and metro
transport, and mobile connectivity all the way to video streaming and similar user …
transport, and mobile connectivity all the way to video streaming and similar user …
Intelligent constellation diagram analyzer using convolutional neural network-based deep learning
An intelligent constellation diagram analyzer is proposed to implement both modulation
format recognition (MFR) and optical signal-to-noise rate (OSNR) estimation by using …
format recognition (MFR) and optical signal-to-noise rate (OSNR) estimation by using …
Modulation format recognition and OSNR estimation using CNN-based deep learning
D Wang, M Zhang, Z Li, J Li, M Fu… - IEEE Photonics …, 2017 - ieeexplore.ieee.org
An intelligent eye-diagram analyzer is proposed to implement both modulation format
recognition (MFR) and optical signal-to-noise rate (OSNR) estimation by using a convolution …
recognition (MFR) and optical signal-to-noise rate (OSNR) estimation by using a convolution …
Machine-learning method for quality of transmission prediction of unestablished lightpaths
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 …
capital importance for an optimized design of optical networks. Due to the continuous …
Resource assignment based on dynamic fuzzy clustering in elastic optical networks with multi-core fibers
Space-division multiplexing elastic optical networks (SDM-EONs) will play an important role
in addressing the increasing Internet traffic, thanks to their spectrum utilization flexibility and …
in addressing the increasing Internet traffic, thanks to their spectrum utilization flexibility and …
Learning process for reducing uncertainties on network parameters and design margins
In this paper, we propose to lower the network design margins by improving the estimation
of the signal-to-noise ratio (SNR) given by a quality of transmission (QoT) estimator, for new …
of the signal-to-noise ratio (SNR) given by a quality of transmission (QoT) estimator, for new …
Monitoring and data analytics for optical networking: benefits, architectures, and use cases
Operators' network management continuously measures network health by collecting data
from the deployed network devices; data is used mainly for performance reporting and …
from the deployed network devices; data is used mainly for performance reporting and …
Accurate quality of transmission estimation with machine learning
I Sartzetakis, K Christodoulopoulos… - Journal of Optical …, 2019 - opg.optica.org
In optical transport networks the quality of transmission (QoT) is estimated before
provisioning new connections or upgrading existing ones. Traditionally, a physical layer …
provisioning new connections or upgrading existing ones. Traditionally, a physical layer …