The project supports collaboration with EURECOM and its members and partners in area of machine learning for optimization of mobile networks. From the scientific point of view, the objective is to develop algorithms and methods for network control and allocation of distributed computing resources in mobile networks with cloud-based architecture encompassing Multi-access Edge Computing and Cloud-RAN and exploit machine learning for image processing and compression.
Device-to-device, Edge computing, Mobility management, Radio resource management, UAVs/Flying base stations, Machine learning
Major results and publications
- IEEE Wireless Communications, 2022.
![[BibTex]](https://6gmobile.fel.cvut.cz/ico/bibtex_icon.png "BibTex")
- IEEE Vehicular Technology Conference (IEEE VTC2022-Spring), 2022.
- IEEE Vehicular Technology Conference (IEEE VTC2022-Spring), 2022.
- US patent with application No. 16/919,990, 2022.
- IEEE Transactions on Wireless Communications, volume 20, no. 7, 2021.
![[pdf]](https://6gmobile.fel.cvut.cz/ico/pdf_icon.png "pdf")
![[doi]](https://6gmobile.fel.cvut.cz/ico/doi_icon.png "doi")
- Date:
- 03/2020 - 12/2024
- Project no.:
- LTT 20004
- Funding:
- Ministry of Education, Youth and Sports
- Budget:
- ~730k EUR
- PI:
- Zdenek Becvar
- Team (6Gm):
- Pavel Mach, Mehyar Najla, Jan Plachy, Aida Madelkhanova, Saleh Nikooroo
- Partners:
- --
- Topics:
- D2D, UAV, MEC, Mobility, RRM, ML
