The laboratory is focused on key aspects and challenges related to future mobile networks and emerging wireless technologies. The 6Gm is oriented mainly on topics related to control layers. This covers mobility and radio resource management for self-organizing and energy efficient networks. Furthermore, we address network architecture including Mobile Edge Computing (MEC), Cloud-Radio Access Netwok (C-RAN) and drones/UAVs. From a perspective of scenarios, the 6Gm research is oriented mainly on scenarios encompassing device-to-device communication, heterogeneous networks, IoT, and vehicular communications. Our research covers theoretical aspects exploiting various optimizations, game theory, and machine learning as well as practical verification in laboratory equipped with hardware and software for emulation of mobile networks.
For cellular networks, mobility is an essential feature. Mobility management procedures at all stages, i.e., scanning of neighborhood, handover decision and call admission control, for future mobile networks cope especially with high density of base stations. The management enabling users’ mobility must guarantee quality required by users in quickly changing environment with heterogeneous services, technologies and cells. Efficient management of such a complex problem can be ensured by self-organizing and optimizing algorithms exploiting prediction and machine learning approaches to estimate future characteristics and behavior of users and network and adapt parameters of mobility management accordingly.