Abstract:
The robustness of a ML-based QoT input parameters refinement technique in partially loaded networks (both static and dynamic) is assessed using experimental data. SNR pre...Show MoreMetadata
Abstract:
The robustness of a ML-based QoT input parameters refinement technique in partially loaded networks (both static and dynamic) is assessed using experimental data. SNR prediction error is reduced by up to 1dB over >40000 services. © 2021 The Author(s)
Date of Conference: 06-10 March 2022
Date Added to IEEE Xplore: 13 April 2022
ISBN Information:
Conference Location: San Diego, CA, USA