Project duration: 01.09.2022 - 31.08.2025

The demand from industry for its own local campus networks is steadily increasing Campus networks enable secure and efficient communication within the company. In the process, it is possible to integrate additional industry-specific functions in customized configurations tailored to the respective user and their needs.

Currently, no architectures and components are available for campus networks that avoid the cost and complexity of public networks and also provide interfaces for additional functions. The products currently available are not optimal for use in campus networks and are inefficient.

The goal of 6G-CAMPUS is to investigate and develop special components and system architectures for use in 6G campus networks and to test their functions in realistic environments. This approach is pursued taking into account technological sovereignty and the special security requirements in campus networks.

Merantix Momentum is pursuing several research questions in 6G-CAMPUS that can be grouped into three distinct areas: Detecting objects and reconstructing scenes in an industrial context, detecting anomalies and improving robustness and data security, and efficiently implementing the developed methods while maintaining limited resources.

Merantix Momentum is involved in the research, development and evaluation of novel Joint Communication and Sensing methods for scene reconstruction and analysis. In this context, the environment can be sensed using machine learning methods based on data communication measurement data. In order to prove the usability of these ML methods, their efficiency, safety as well as robustness against disturbance factors are evaluated.

‍