5G6GArchitectureD2DMECML/AIRRMCooperation with the International Research Centre in Area of Communication Systems

Exploitation of machine learning for optimization of mobile networks

The project supports collaboration with EURECOM and its partners in area of machine learning and estimation for optimization of mobile networks. From the scientific point of view, the objective is to develop algorithms and methods for radio resource allocation and computing resource allocation in mobile networks with cloud-based architecture encompassing Multi-access Edge Computing and Cloud-RAN.

Radio resource management, Mobile Edge Computing, Machine learning

Major results and publications

  • , , and
    Dynamic Allocation of Computing and Communication Resources in Multi-Access Edge Computing for Mobile Users
    IEEE Transactions on Network and Service Management, .

    [BibTex] [pdf] [doi]
  • , and
    Incentive-based D2D Relaying in Cellular Networks
    IEEE Transactions on Communications, volume 69, no. 3, .

    [BibTex]
  • , , and
    Predicting Device-to-Device Channels from Cellular Channel Measurements: A Learning Approach
    IEEE Transactions on Wireless Communications, volume 19, no. 11, .

    [BibTex] [pdf]
  • , and
    Incentive Mechanism and Relay Selection for D2D Relaying in Cellular Networks
    IEEE Global Communications Conference (IEEE Globecom 2019), .

    [BibTex]
  • , , , and
    Two-Phase Random Access Procedure for LTE-A Networks
    IEEE Transactions on Wireless Communications, volume 18, no. 4, .

    [BibTex]

    Date:
    01/2017 – 12/2019
    Project no.:
    LTT 18007
    Funding:
    Ministry of Education, Youth and Sports
    Budget:
    ~250k EUR
    PI:
    Zdenek Becvar
    Team:
    Pavel Mach, Mehyar Najla, Jan Plachy
    Partners:
    --