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

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 …

Optical networks generate a vast amount of diagnostic, control, and performance monitoring
data. When information is extracted from these data, reconfigurable network elements and …

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 …

Digital twin (DT) has revolutionized optical communication networks by enabling their full life-
cycle management, including planning, prediction, optimization, upgrade, and …

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 …

We present a framework for enhancing Gaussian process regression machine learning
models with a priori knowledge derived from models of the transmission physics in optical …

We propose a technique for modeling erbium-doped fiber amplifiers (EDFAs) in optical fiber
networks, where the amplifier unit is located at a distant node outside the laboratory. We …

Network design margins are introduced by quality of transmission estimator inaccuracies.
Some of those inaccuracies are due to uncertainty on the fiber type deployed in optical …

Over the years, optical communication systems have been a significant source of fast and
secure communication. However, factors like noise and mitigation error can degrade the bit …