Integration of Scaled Real-world Testbeds with Digital Twins for Future AI-Enabled 6G Networks

Future 6G communication systems need to be carefully evaluated under near real-life boundary conditions to prove their performance beyond theoretical considerations and simulations. In this work, we propose a new, lean approach to integrate and evaluate future 6G network architectures and AI-enabled approaches in scaled physical environments that emulate the full-scale communication, mobility, and environmental conditions powered by a Digital Network Twin (DNT). Our approach is enabled by the realistic modeling of the radio environmental impacts within the DNT, such as path loss, shadowing, and interference. One key contribution lies in the specific communication emulation functionality embedded in the real-time capable DNT, which allows imposing specific communication technology properties of the real-life scenario on the scaled physical environment. In this paper, we introduce a prototyping architecture and present a comprehensive case study to demonstrate the effectiveness of the approach: the AI-enabled mesh routing protocol PARRoT is evaluated in three scaled scenarios (teleoperation, platooning, and intralogistic transport). The results show that future 6G networks can be evaluated in realistic, yet safe and cost-efficient environments before moving onto the real world.