The research area focuses on advanced Mobile Radio Networks and next-generation cellular systems, addressing both theoretical and experimental challenges in 5G and 6G scenarios. Core activities include radio network planning and optimization, the design of efficient radio resource management (RRM) algorithms, and the study of innovative network architectures. Particular attention is devoted to emerging paradigms such as smart radio environments, where reconfigurable intelligent surfaces and programmable propagation are integrated into the network design. The research also investigates interference management techniques, including complex spectrum sharing scenarios involving heterogeneous networks and dynamic spectrum access.
A significant research thrust concerns data-driven network management. This includes the statistical analysis of network counters and Key Performance Indicators (KPIs), as well as the development of machine learning-based methods for performance prediction, anomaly detection, traffic forecasting, and self-optimization. AI-based approaches to network automation are explored to enable self-organizing and self-healing networks, reducing operational costs while improving reliability and quality of service. In parallel, the group studies digital twin-based solutions for network control and management, where virtual replicas of physical networks are used to test optimization strategies, evaluate what-if scenarios, and support real-time decision-making.
Methodologically, the research combines analytical modeling with extensive simulation and prototyping. Optimization theory and game-theoretic models are employed to design distributed and scalable algorithms for resource allocation, interference coordination, and spectrum sharing. System-level simulations are conducted using platforms such as ns-3 and NVIDIA Sionna RT, enabling performance evaluation under realistic conditions. Furthermore, developed solutions are validated through prototypical implementations using open-source Software Defined Radio (SDR) platforms, including OpenAirInterface and similar frameworks, allowing experimental assessment in controlled and real-world environments.
