Cooperation with the International Research Centre in Area of Digital Communication Systems

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

M. Nikooroo, Z. Becvar, O. Esrafilian and D. Gesbert
Channel Reuse for Backhaul in UAV Mobile Networks with User QoS Guarantee
IEEE International Conference on Communications (IEEE ICC 2023), 2023.
A. Doostmohammadi, M.R. Khayyambashi, N. Movahedinia and Z. Becvar
Dynamic Clustering for Low Delay Delivery of Video Content Cached in MEC Servers
IEEE Systems Journal, volume Early access, 2023.
A. Madelkhanova, Z. Becvar and T. Spyropoulos
Optimization of Cell Individual Offset for Handover of Flying Base Stations and Users
IEEE Transactions on Wireless Communications, volume 22, no. 5, 2023.
M. Nikooroo and Z. Becvar
Maximization of Minimum User Capacity in UAV-Enabled Mobile Networks with NOMA
IEEE Networking Letters, volume 5, no. 1, 2023.
M. Ruzicka, Z. Becvar and J. Gajda
Energy Consumption Optimization for UAV Base Stations with Wind Compensation
IEEE Communications Letters, volume 27, no. 3, 2023.
Z. Becvar, D. Gesbert, P. Mach and M. Najla
Machine Learning-based Channel Quality Prediction in 6G Mobile Networks
IEEE Communications Magazine, 2023.
P. Mach, Z. Becvar and T. Spyropoulos
Coping with Spatial Unfairness and Overloading Problem in Mobile Networks via D2D Relaying
IEEE Wireless Communications, 2022.
M. Nikooroo, O. Esrafilian, Z. Becvar and D. Gesbert
Sum Capacity Maximization in Multi-Hop Mobile Networks with Flying Base Stations
IEEE Global Communications Conference (IEEE GLOBECOM 2022), 2022.
I. Ahmad, R. Narmeen, Z. Becvar and I. Guvenc
Machine Learning-Based Beamforming for Unmanned Aerial Vehicles Equipped with Reconfigurable Intelligent Surfaces
IEEE Wireless Communications, volume 29, no. 4, 2022.
Z. Becvar, M. Nikooroo and P. Mach
On Energy Consumption of Airship-based Flying Base Stations Serving Mobile Users
IEEE Transactions on Communications, volume 70, no. 10, 2022.
M. Nikooroo, Z. Becvar, O. Esrafilian and D. Gesbert
QoS-Aware Sum Capacity Maximization for Mobile Internet of Things Devices Served by UAVs
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.
P. Mach and Z. Becvar
Device-to-Device Relaying: Optimization, Performance Perspectives, and Open Challenges towards 6G Networks
IEEE Communications Surveys & Tutorials, 2022.
A. Madelkhanova, Z. Becvar and T. Spyropoulos
Q-Learning-based Setting of Cell Individual Offset for Handover of Flying Base Stations
IEEE Vehicular Technology Conference (IEEE VTC2022-Spring), 2022.
M. Najla, Z. Becvar, P. Mach and D. Gesbert
System and Methods for Device-to-Device Communication
US patent No. US11284361B2, 2022.
M. Najla, Z. Becvar and P. Mach
Reuse of Multiple Channels by Multiple D2D Pairs in Dedicated Mode: Game Theoretic Approach
IEEE Transactions on Wireless Communications, volume 20, no. 7, 2021.

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

-Ongoing-6G D2D MEC ML/AI Mobility RRM UAVCooperation with the International Research Centre in Area of Digital Communication Systems

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