prof. Ing. Zdeněk Bečvář, Ph.D.

The objective is to propose algorithms for allocation of cloud computing and radio communication resources allowing simultaneously real-time control of the radio access network and efficient processing of mobile users’ applications in the cloud deployed in mobile networks. This includes a combination of mobile edge computing (MEC) concept and cloud control of radio access network (C-RAN) in terms of a dynamic allocation of cloud resources for processing of individual user and network control tasks. The proposed algorithm should be able to predict the most suitable place for deployment of computation and migrate it if it is beneficial. https://comtel.fel.cvut.cz/cs/users/becvaz1

The topic focuses on a design of advanced radio resource and mobility management algorithms for 6G mobile networks with a flexible architecture with clouds. The designed algorithms should improve network throughput via dynamic and self-optimized solutions exploiting machine learning tools. The proposed solutions should reflect requirements on future mobile networks including high throughput, very low latency, and/or very low energy consumption even in the scenarios with massive amount of mobile devices and architecture with slicing and encompassing flying base stations and/or flying user equipment.

The objective is to design algorithms exploiting prediction for mobility management in future mobile networks with flexible architecture of radio access network. Then, the mobility management should be optimized taking into account an impact of the mobility management on the users' and network's performances. This includes design of a dynamic selection of neighboring cells to which the user can perform handover and selection of the most suitable serving cell with respect to type of service, behavior of users and networks status. https://comtel.fel.cvut.cz/cs/users/becvaz1

The objective is to propose a solution for allocation of communication and computing resources for processing of user data as well as environment and vehicles’ information. The developed solution should provide reliable and efficient allocation of both communication as well as computation resources suitable for processing of information in various scenarios including road safety. The communication among vehicles as well as with an infrastructure is based on mobile networks.