-Ongoing-6GD2DMECML/AIMobilityRRMUAVCooperation with the International Research Centre in Area of Digital Communication Systems

Machine learning for mobile network optimization and for image processing

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

  • , and
    Optimization of Cell Individual Offset for Handover of Flying Base Stations and Users
    IEEE Transactions on Wireless Communications, .

    [BibTex]
  • , , and
    Sum Capacity Maximization in Multi-Hop Mobile Networks with Flying Base Stations
    IEEE Global Communications Conference (IEEE GLOBECOM 2022), .

    [BibTex]
  • and
    Maximization of Minimum User Capacity in UAV-Enabled Mobile Networks with NOMA
    IEEE Networking Letters, .

    [BibTex]
  • , , and
    Machine Learning-Based Beamforming for Unmanned Aerial Vehicles Equipped with Reconfigurable Intelligent Surfaces
    IEEE Wireless Communications, volume 29, no. 4, .

    [BibTex] [pdf] [doi]
  • , and
    On Energy Consumption of Airship-based Flying Base Stations Serving Mobile Users
    IEEE Transactions on Communications, volume 70, no. 10, .

    [BibTex] [pdf] [doi]
  • , , and
    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, .

    [BibTex]
  • and
    Device-to-Device Relaying: Optimization, Performance Perspectives, and Open Challenges towards 6G Networks
    IEEE Communications Surveys & Tutorials, .

    [BibTex] [pdf] [doi]
  • , and
    Q-Learning-based Setting of Cell Individual Offset for Handover of Flying Base Stations
    IEEE Vehicular Technology Conference (IEEE VTC2022-Spring), .

    [BibTex] [pdf]
  • , , and
    System and Methods for Device-to-Device Communication
    US patent No. US11284361B2, .

    [BibTex]
  • , and
    Reuse of Multiple Channels by Multiple D2D Pairs in Dedicated Mode: Game Theoretic Approach
    IEEE Transactions on Wireless Communications, volume 20, no. 7, .

    [BibTex] [pdf] [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

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