[HTML][HTML] Orbital angular momentum and beyond in free-space optical communications
Orbital angular momentum (OAM), which describes tailoring the spatial physical dimension
of light waves into a helical phase structure, has given rise to many applications in optical …
of light waves into a helical phase structure, has given rise to many applications in optical …
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) …
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 …
End-to-end deep learning of optical fiber communications
In this paper, we implement an optical fiber communication system as an end-to-end deep
neural network, including the complete chain of transmitter, channel model, and receiver …
neural network, including the complete chain of transmitter, channel model, and receiver …
[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 …
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 …
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 …
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 …
Performance limits in optical communications due to fiber nonlinearity
In this paper, we review the historical evolution of predictions of the performance of optical
communication systems. We will describe how such predictions were made from the outset …
communication systems. We will describe how such predictions were made from the outset …
[HTML][HTML] Photonic machine learning implementation for signal recovery in optical communications
Abstract Machine learning techniques have proven very efficient in assorted classification
tasks. Nevertheless, processing time-dependent high-speed signals can turn into an …
tasks. Nevertheless, processing time-dependent high-speed signals can turn into an …