The use of AI/ML-based strategies that require little or no prior information increases the efficiency of technological networks in terms of several performance metrics. For example, they reduce signaling and feedback overhead, improve security and privacy, and are compatible with the self-interest of devices, vendors, and stakeholders. Nevertheless, the algorithmic decision strategies must adapt to the physical properties of the problem and the specific nature of the communication medium. For example, in wireless networks, the interference, changes in channel quality, and hardware limitations exacerbate the problem.
The core contribution of this project is the development of AI/ML-based decision strategies for application in wireless networks. Such methods shall be robust against information scarcity and amenable to distributed implementation. In particular, the goal is to apply the theoretical schemes to solve several research problems at different network layers, including radio resource management, joint communications and sensing, function placement, multi-connectivity, and beam selection.
This project is a part of the 6G-Research and Innovation Cluster. The research hub consists of several partners, including universities and research institutes. Besides, many industry partners support the project.

The project receives funding from the German Ministry of Education and Research. The duration is 08.2021-07.2025.

More information can be found here: https://6g-ric.de