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 …

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 …

For reliable and efficient network planning and operation, accurate estimation of Quality of
Transmission (QoT) before establishing or reconfiguring the connection is necessary. In …

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 …

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

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 …

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 …

Increasing traffic demands are causing network operators to adopt disaggregated and open
networking solutions to better exploit optical transmission capacity, and consequently …

We report a neural-network based erbium-doped fiber amplifier (EDFA) gain model built
from experimental measurements. The model shows low gain-prediction error for both the …

In this article, machine learning is used to create a differentiable model for the input-output
power spectral profile relations of C-band erbium-doped fiber amplifiers (EDFAs). The EDFA …