Machine learning techniques for optical performance monitoring and modulation format identification: A survey
The trade-off between more user bandwidth and quality of service requirements introduces
unprecedented challenges to the next generation smart optical networks. In this regard, the …
unprecedented challenges to the next generation smart optical networks. In this regard, the …
AI-based modeling and monitoring techniques for future intelligent elastic optical networks
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 …
capacity demand for optical networks has been increasing dramatically. To fulfill the capacity …
Artificial intelligence based quality of transmission predictive model for cognitive optical networks
Due to the advancements in 5 G technologies, high-definition, and the internet of things
(IoT), the capacity demand of optical networks has been exponentially increased. Optical …
(IoT), the capacity demand of optical networks has been exponentially increased. Optical …
Machine learning techniques for quality of transmission estimation in optical networks
Y Pointurier - Journal of Optical Communications and …, 2021 - ieeexplore.ieee.org
The estimation of the quality of transmission (QoT) in optical systems with machine learning
(ML) has recently been the focus of a large body of research. We discuss the sources of …
(ML) has recently been the focus of a large body of research. We discuss the sources of …
Transfer learning for neural networks-based equalizers in coherent optical systems
In this work, we address the question of the adaptability of artificial neural networks (NNs)
used for impairments mitigation in optical transmission systems. We demonstrate that by …
used for impairments mitigation in optical transmission systems. We demonstrate that by …
A survey on QoT prediction using machine learning in optical networks
In optical networks, a connection (eg, light-path and light-tree) is set up to carry data from its
source to destination (s). When the optical signal transmits through the fiber links and optical …
source to destination (s). When the optical signal transmits through the fiber links and optical …
Feedforward and recurrent neural network-based transfer learning for nonlinear equalization in short-reach optical links
Neural network (NN)-based nonlinear equalizers have been shown effective for various
types of short-reach direct detection systems. However, they work best for a certain channel …
types of short-reach direct detection systems. However, they work best for a certain channel …
Survey on the use of machine learning for quality of transmission estimation in optical transport networks
Estimating the Quality of Transmission (QoT) of the optical signal from source to destination
nodes is the cornerstone of design engineering and service provisioning in optical transport …
nodes is the cornerstone of design engineering and service provisioning in optical transport …
Optical performance monitoring in mode division multiplexed optical networks
This article considers, for the first time, optical performance monitoring (OPM) in few mode
fiber (FMF)-based optical networks. 1-D features vector, extracted by projecting a 2-D …
fiber (FMF)-based optical networks. 1-D features vector, extracted by projecting a 2-D …
Comparison of domain adaptation and active learning techniques for quality of transmission estimation with small-sized training datasets
Machine learning (ML) is currently being investigated as an emerging technique to automate
quality of transmission (QoT) estimation during lightpath deployment procedures in optical …
quality of transmission (QoT) estimation during lightpath deployment procedures in optical …