RESOURCES
Standard presentation [EN]
Project leaflet [EN]
Standard presentation [EN]
Project leaflet [EN]
➡️ Goez, D., Aycan-Beyazit, E., Slamnik-Kriještorac, N., Marquez-Barja, J., Gaviria, N., Latré, S., & Camelo, M. (2024). Computational Efficiency of Deep Learning-Based Super Resolution Methods for 5G-NR Channel Estimation. Zenodo.
https://doi.org/10.5281/zenodo.13938898
➡️ Jimenez, J., Gavrielides, A., Slamnik-Kriještorac, N., Latré, S., Marquez-Barja, J., & Camelo, M. (2024). Integrating AI Orchestration and Lifecycle Management in 6G Networks: A Pipeline Approach. Zenodo.
https://doi.org/10.5281/zenodo.13938811
➡️ Troch, A., Limani, X., Camelo, M., Gavrielides, A., Chang, C.-Y., Marquez-Barja, J., & Peeters, M. (2024). Optimizing Radio Resource Allocation in 5G using Transport Network-Aware Intelligent RAN. Zenodo.
https://doi.org/10.5281/zenodo.13938570
➡️ Faye, S., Camelo, M., Sottet, J.-S., Sommer, C., Franke, M., Baudouin, J., Castellanos, G., Decorme, R., Fanti, M. P., Fuladi, R., Kesik, G., Mendes, B., Murphy, C., Parker, S., Pryor, S., Senouci, S. M., & Turcanu, I. (2024, July 3). Integrating Network Digital Twinning into Future AI-based 6G Systems: The 6G-TWIN Vision. EuCNC & 6G Summit 2024 (EUCNC), Antwerp, Belgium.
https://doi.org/10.5281/zenodo.12635245
➡️ Turcanu, I., Faye, S., Fellner, H., Castellanos, G., Baudouin, J., Senouci, S. M., Franke, M., & Sommer, C. (2024). Digital Twinning for 6G Teleoperated Driving: The 6G-TWIN Vision. EuCNC & 6G Summit 2024 (EUCNC), Antwerp, Belgium. Zenodo.
https://doi.org/10.5281/zenodo.12635133
D6.1 – 6G-TWIN project identity
D1.1 – 6G-TWIN architecture and technical foundations (initial)
D2.1 – Data governance, privacy and harmonization
D7.2 – Data management plan
D1.2 – Secured, scalable and distributed data exposure and collection framework (initial)
D2.2 – Basic models (initial)
D5.1 – Evaluation methodology, planning and coordination
D2.3 – Functional models (initial)
D1.3 – Frameworks for zero-touch service and network management and the orchestration of its AI-based NF and NS (initial)
D4.1 – Setup of the 6G-TWIN demonstrators
D3.1 – Federated simulation framework
D4.2 – Testbed findings and data analytics
D5.2 – Evaluation deployment report
D1.4 – 6G-TWIN architecture and technical foundations (final)
D1.5 – Secured, scalable and distributed data exposure and collection framework (final)
D1.6 – Frameworks for zero-touch service and network management and the orchestration of its AI-based NF and NS (final)
D2.4 – Basic models (final)
D2.5 – Functional models (final)
D3.2 – Federated simulation framework evaluation report
D5.3 – Reengineering solutions
D5.4 – Standardisation
Co-funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or Smart Networks and Services Joint Undertaking. Neither the European Union nor the granting authority can be held responsible for them.