Archivio Istituzionale della RicercaWe propose a machine learning-based technique that accurately estimates quality-of-transmission (QoT) impairments of an optical switch on 400ZR. The proposed scheme works in an entirely agnostic way reduces inaccuracy in QoT impairments estimation by 1.5 dB.
Machine learning Assisted Accurate Estimation of QoT Impairments of Photonics Switching System on 400ZR / Khan, Ihtesham; Tunesi, Lorenzo; Masood, Muhammad Umar; Ghillino, Enrico; Bardella, Paolo; Carena, Andrea; Curri, Vittorio.. - ELETTRONICO. - (2021). (Intervento presentato al convegno Asia Communications and Photonics tenutosi a Shanghai, China nel 24–27 October 2021) [10.1364/ACPC.2021.T2B.2].
Machine learning Assisted Accurate Estimation of QoT Impairments of Photonics Switching System on 400ZR
Khan, Ihtesham;Tunesi, Lorenzo;Masood, Muhammad Umar;Bardella, Paolo;Carena, Andrea;Curri, Vittorio.
2021
Abstract
We propose a machine learning-based technique that accurately estimates quality-of-transmission (QoT) impairments of an optical switch on 400ZR. The proposed scheme works in an entirely agnostic way reduces inaccuracy in QoT impairments estimation by 1.5 dB.
| File | Dimensione | Formato | |
|---|---|---|---|
|
ACPC-2021-T2B.2.pdf
accesso riservato
Tipologia:
2a Post-print versione editoriale / Version of Record
Licenza:
Non Pubblico - Accesso privato/ristretto
Dimensione
480.63 kB
Formato
Adobe PDF
|
480.63 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
|
C_ACP_Rejected_C_ECOC_Machine_learning_Assisted_Accurate_Estimation_of_QoT_Impairments_of_Photonics_Switching_System_on_400ZR_V1_19072021 (3).pdf
Open Access dal 28/10/2022
Tipologia:
2. Post-print / Author's Accepted Manuscript
Licenza:
Pubblico - Tutti i diritti riservati
Dimensione
397.63 kB
Formato
Adobe PDF
|
397.63 kB | Adobe PDF | Visualizza/Apri |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/11583/2949516