Filtering Impairments-Aware Digital Twin for SNR Prediction over Network Life-Cycle
We propose a new method to improve SNR prediction of existing and new services with the presence of unknown penalties due to filtering effects. We validate the method in a testbed experiment with 5 OMS and up to 200 deployed services and show an average improvement of SNR service prediction of up to 0.9dB.
Authors
- Gabriel Charlet (ORCID: https://orcid.org/0000-0003-1398-5446)
- Xin Yang (ORCID: https://orcid.org/0000-0002-7542-054X)
- Reda Ayassi (ORCID: https://orcid.org/0000-0003-3777-2445)
- Yvan Pointurier (ORCID: https://orcid.org/0000-0002-7612-4814)
- Chenyu Sun (ORCID: https://orcid.org/0000-0002-6391-2635)
Institutions
- Huawei Technologies (France) (FR)
Publication Details
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1364/ofc.2025.w4g.4
- Primary Topic
- Advanced Data and IoT Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00