Machine learning based linear and nonlinear noise estimation

FJV Caballero, DJ Ives, C Laperle… - Journal of Optical …, 2018 - opg.optica.org
Operators are pressured to maximize the achieved capacity over deployed links. This can be
obtained by operating in the weakly nonlinear regime, requiring a precise understanding of …

Distributed abstraction and verification of an installed optical fibre network

DJ Ives, S Yan, L Galdino, R Wang, DJ Elson… - Scientific Reports, 2021 - nature.com
The management of wavelength routed optical mesh networks is complex with many
potential light path routes and numerous physical layer impairments to transmission …

Gaussian process-driven history matching for physical layer parameter estimation in optical fiber communication networks

JW Nevin, S Nallaperuma, SJ Savory - arXiv preprint arXiv:2202.11700, 2022 - arxiv.org
We present a methodology for the estimation of optical network physical layer parameters
from signal to noise ratio via history matching. An expensive network link simulator is …

A comparison of impairment abstractions by multiple users of an installed fiber infrastructure

DJ Ives, S Yan, L Galdino, DJ Elson… - Optical Fiber …, 2019 - opg.optica.org
A Comparison of Impairment Abstractions by Multiple Users of an Installed Fiber Infrastructure
Page 1 M4J.4.pdf OFC 2019 © OSA 2019 A Comparison of Impairment Abstractions by …

Machine learning for optical fibre communication systems

J Nevin - 2023 - repository.cam.ac.uk
Global demand for internet traffic is growing at a rapid rate, driven by the adoption of new
technologies and increased demand from consumers. This continued growth is exerting …

Noise metrology in optical communication systems

FJ Vaquero Caballero - 2021 - repository.cam.ac.uk
Noise Metrology in Optical Communication Systems Page 1 Noise Metrology in Optical
Communication Systems FJ Vaquero-Caballero Department of Engineering University of …