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 Transactions on Wireless Communications, 2022.
- IEEE Global Communications Conference (IEEE GLOBECOM 2022), 2022.
- IEEE Networking Letters, 2022.
- IEEE Wireless Communications, volume 29, no. 4, 2022.
- IEEE Transactions on Communications, volume 70, no. 10, 2022.
- IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (IEEE PIMRC 2022) workshop on Sustainable and Intelligent Green Internet of Things for 6G and Beyond, 2022.
- IEEE Communications Surveys & Tutorials, 2022.
- IEEE Vehicular Technology Conference (IEEE VTC2022-Spring), 2022.
- US patent No. US11284361B2, 2022.
- IEEE Transactions on Wireless Communications, volume 20, no. 7, 2021.
- 03/2020 - 12/2024
- Project no.:
- LTT 20004
- Ministry of Education, Youth and Sports
- ~730k EUR
- Zdenek Becvar
- Team (6Gm):
- Pavel Mach, Mehyar Najla, Jan Plachy, Aida Madelkhanova, Saleh Nikooroo
- D2D, UAV, MEC, Mobility, RRM, ML