5Gain: 5G Infrastructures for local energy systems using artificial intelligence
The main objectives of the 5Gain project are the development and evaluation of concepts for cellular energy systems, whose regional extraction and production behavior is optimized by means of machine learning methods. Therefore, novel 5G mobile radio networks enable dynamic, dedicated allocation of location-based transmission resources based on shared communication infrastructures (regional network slices) for energy system applications via the use of network slicing.
CNI focuses on the conceptual design of AI procedures for the network management of cellular energy systems, as well as the development of an end-to-end 5G Regional Network system for dynamic, location-specific resource allocation.
Project duration: 01.12.2019 - 31.05.2023
The project is funded by the Federal Ministry for Economic Affairs and Energy under the funding reference 03EI6018C.
News
Publications
Towards Open 6G: Experimental O-RAN Framework for Predictive Uplink Slicing
R. Wiebusch, N. A. Wagner, D. Overbeck, F. Kurtz, C. Wietfeld
In 2023 IEEE International Conference on Communications (ICC), Rome, Italy, May 2023.
Context-based Latency Guarantees Considering Channel Degradation in 5G Network Slicing
A. Nota, S. Saidi, D. Overbeck, F. Kurtz, C. Wietfeld
In 2022 IEEE Real-Time Systems Symposium (RTSS), USA, December 2022.
Proactive Resource Management for Predictive 5G Uplink Slicing
D. Overbeck, N. A. Wagner, F. Kurtz, C. Wietfeld
In 2022 IEEE Global Communications Conference (GLOBECOM), December 2022, Brazil.
Design of a 5G Network Slicing Architecture for Mixed-Critical Services in Cellular Energy Systems
D. Overbeck, F. Kurtz, S. Böcker, C. Wietfeld
In 2022 IEEE SmartGridComm, Singapore, October 2022.
Software-Defined Networking driven Time-Sensitive Networking for Mixed-Criticality Control Applications
F. Kurtz, et al.
In International Conference on Information and Communication Technology Convergence (ICTC), IEEE, Jeju-si, KOR, October 2022.
Predictive 5G Uplink Slicing for Blockchain-driven Smart Energy Contracts
F. Kurtz, R. Wiebusch, D. Overbeck, C. Wietfeld
In IEEE International Conference on Communications (ICC) 2022
SAMUS: Slice-Aware Machine Learning-based Ultra-Reliable Scheduling
C. Bektas, D. Overbeck, C. Wietfeld
In 2021 IEEE International Conference on Communications (ICC), Virtual Event, June 2021
Building End-to-end IoT Applications with QoS Guarantees (Invited Paper)
A. Hamann, D. Ginthoer, D. Ziegenbein, S. Saidi, C. Wietfeld, A. Rowe
In Design Automation Conference 2020, IEEE, San Francisco, USA, July 2020