A contemporary survey on free space optical communication: Potentials, technical challenges, recent advances and research direction
Due to the unprecedented growth of high speed multimedia services and diversified
applications initiated from the massive connectivity of IoT devices, 5G and beyond 5G (B5G) …
applications initiated from the massive connectivity of IoT devices, 5G and beyond 5G (B5G) …
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 …
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 …
Joint atmospheric turbulence detection and adaptive demodulation technique using the CNN for the OAM-FSO communication
J Li, M Zhang, D Wang, S Wu, Y Zhan - Optics express, 2018 - opg.optica.org
A novel joint atmospheric turbulence (AT) detection and adaptive demodulation technique
based on convolutional neural network (CNN) are proposed for the OAM-based free-space …
based on convolutional neural network (CNN) are proposed for the OAM-based free-space …
Failure prediction using machine learning and time series in optical network
In this paper, we propose a performance monitoring and failure prediction method in optical
networks based on machine learning. The primary algorithms of this method are the support …
networks based on machine learning. The primary algorithms of this method are the support …
Building a digital twin for intelligent optical networks [Invited Tutorial]
To support the development of intelligent optical networks, accurate modeling of the physical
layer is crucial. Digital twin (DT) modeling, which relies on continuous learning with real-time …
layer is crucial. Digital twin (DT) modeling, which relies on continuous learning with real-time …
A survey on deep learning techniques in wireless signal recognition
X Li, F Dong, S Zhang, W Guo - Wireless Communications and …, 2019 - Wiley Online Library
Wireless signal recognition plays an important role in cognitive radio, which promises a
broad prospect in spectrum monitoring and management with the coming applications for …
broad prospect in spectrum monitoring and management with the coming applications for …
Compensation of fiber nonlinearities in digital coherent systems leveraging long short-term memory neural networks
We introduce for the first time the utilization of Long short-term memory (LSTM) neural
network architectures for the compensation of fiber nonlinearities in digital coherent systems …
network architectures for the compensation of fiber nonlinearities in digital coherent systems …
A review of machine learning-based failure management in optical networks
Failure management plays a significant role in optical networks. It ensures secure operation,
mitigates potential risks, and executes proactive protection. Machine learning (ML) is …
mitigates potential risks, and executes proactive protection. Machine learning (ML) is …
Application of a convolutional neural network in permeability prediction: A case study in the Jacksonburg-Stringtown oil field, West Virginia, USA
Permeability is a critical parameter for understanding subsurface fluid flow behavior,
managing reservoirs, enhancing hydrocarbon recovery, and sequestering carbon dioxide. In …
managing reservoirs, enhancing hydrocarbon recovery, and sequestering carbon dioxide. In …