This paper explores the significance of Quality of Transmission (QoT) estimation in optical
networks and highlights the increasing use of machine learning (ML) techniques to enhance …

Optical network automation requires accurate physical layer models, not only for
provisioning but also for real-time analysis. In particular, in-phase (I) and quadrature (Q) …

The introduction of 5G, the increasing number of connected devices, and the exponential
growth of services relying on connectivity are pressuring multilayer networks to improve their …

There has been an increase in demand of optical networks over the recent years due to
which they have become sources of heterogeneous data. Several other challenges such as …

The popularity of high-capacity communication services such as video streaming and cloud
computing has accelerated the growth in IP traffic. In order to effectively manage and …

Machine learning (ML) has disrupted a wide range of science and engineering disciplines in
recent years. ML applications in optical communications and networking are also gaining …

Optical communication networks have played and will continue to play a prominent role in
the development and deployment of network infrastructures. The optical systems and …

Machine learning (ML) has achieved phenomenal success in revolutionizing a number of
science and engineering disciplines over the last decade. Naturally, it is also being …