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 …

We investigate quality of transmission (QoT) estimation in a multi-band transmission
scenario, including a wideband description of the frequency-dependent physical layer …

With the rapid development of virtual/augmented reality and cloud services, the capacity
demand for optical communication systems is ever-increasing. To further increase system …

Estimating the quality of transmission (QoT) of a candidate lightpath prior to its establishment
is of pivotal importance for effective decision making in resource allocation for optical …

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 …

In this paper, we show that by combining experimental data from different optical fibers, we
can build a fiber-agnostic neural-network to model the Raman amplifier. The fiber-agnostic …

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 …

By associating machine learning and an analytical model (ie, the Gaussian noise model),
we reduce uncertainties on the output power profile and the noise figure of each amplifier in …

Optical transmission systems with high spectral efficiency require accurate quality of
transmission estimation for optical channel provisioning. However, the wavelength …

Wireless traffic will significantly increase in next-generation networks. Therefore, there is a
need for novel optical network front-/mid-/backhaul (x-haul) architectures that can deliver …