Real-Time Virtualization for Industrial 6G Applications

Project Goal

Project VICTOR6G (Real-Time Virtualization for Industrial 6G Applications) aims at developing solutions where applications interact with integrated 6G-wireless and wired networks, taking into account both existing and future production environments. The main innovation would be the interaction of both, networks and applications, to consensually adapt to dynamically changing situations. While the project primarily targets industrial production landscapes, the resulting solutions will also be applicable across other sectors.

The project pursues application-independent, systemic interaction of digital twins of both the application and the network under the paradigm of Industrial Metaverse, as well as the seamless interaction of 6G-wireless and wired Time Sensitive Networking (TSN) with flexible use of several frequency ranges (FR1-FR3) with central orchestration. For example, the network can be informed that an overhead crane will soon block a radio cell. The network can react to this by dynamically using other frequency ranges that are more robust against obstruction for all or selected data streams. Alternatively, or complementary, an application could adapt and postpone non-time-critical communication of large data amounts.

The use cases considered in the project are time-critical control loops realized through Programmable Logic Controllers (PLCs) and outsourcing computationally intensive tasks from the end devices, such as a drone, to the (edge) cloud. Some of these applications are already possible with 5G networks, but embedding them in an Industrial Metaverse, where digital twins of applications interact and augmented reality enhances user experience, results in more cost- and energy-efficient solutions.

Industrial Metaverse

Digital twins of application and network interact systemically, supported by AI-driven decision-making algorithms.

Integrated Networks

Seamless integration of 6G-wireless and wired TSN with flexible use of frequency ranges including FR1, FR2, and FR3.

AI-Driven Optimization

Artificial Intelligence derives adaptation and optimization decisions from the current state of both the production process and the network.