Today's telecommunication networks have become sources of enormous amounts of widely
heterogeneous data. This information can be retrieved from network traffic traces, network …

Failure management plays a role of capital importance in optical networks to avoid service
disruptions and to satisfy customers' service level agreements. Machine learning (ML) …

Leveraging Deep Learning to Achieve Efficient Resource Allocation with Traffic Evaluation in
Datacenter Optical Networks Page 1 W4I.2.pdf OFC 2018 © OSA 2018 Leveraging Deep …

We investigate the capacity improvement achieved by bandwidth variable transceivers
(BVT) in meshed optical networks with cascaded ROADM filtering at fixed channel spacing …

A deep neural network (DNN) is employed for optical performance monitoring. We show that
DNN-based monitor successfully estimates OSNR of signals modulated in different formats …

Abstract Machine Learning is an application of artificial intelligence that provides systems
the ability to automatically learn and improve from experience without being explicitly …

Dense wavelength-division multiplexing is conceived as an appropriate solution for the 5G
fronthaul system to cope with the rapidly increasing demand for bandwidth. While the cross …

Supervised machine learning methods are applied and demonstrated experimentally for
inband OSNR estimation and modulation format classification in optical communication …

As the world advances into 5G networks, significant scientific research accomplishments are
being conducted for a communication system that could further enhance the current limit of …

Machine learning techniques have recently received significant attention as promising
approaches to deal with the optical channel impairments, and in particular, the nonlinear …