Abstract
Estimating the quality of transmission (QoT) for lightpaths is crucial for reducing provisioned margins. We investigate an artificial neural network framework to estimate the QoT of unestablished lightpaths considering interference effects and optical monitoring uncertainties.
© 2018 The Author(s)
PDF ArticleMore Like This
I. Sartzetakis, K. Christodoulopoulos, C. P. Tsekrekos, D. Syvridis, and E. Varvarigos
Tu3F.2 Optical Fiber Communication Conference (OFC) 2016
Dong Fu, Min Zhang, Bo Xu, Baojian Wu, and Kun Qiu
Th2I.8 Conference on Lasers and Electro-Optics/Pacific Rim (CLEO/PR) 2018
Omran Ayoub, Andrea Bianco, Davide Andreoletti, Sebastian Troia, Silvia Giordano, and Cristina Rottondi
M3F.5 Optical Fiber Communication Conference (OFC) 2022