Collaborative Research Center 876
The collaborative research center SFB876 brings together data mining and embedded systems. On the one hand, embedded systems can be further improved using machine learning. On the other hand, data mining algorithms can be realized in hardware, e.g. FPGAs, or run on GPGPUs. The restrictions of ubiquitous systems in computing power, memory, and energy demand new algorithms for known learning tasks. These resource bounded learning algorithms may also be applied on extremely large data bases on servers.
Project duration: 01.01.2015 - 31.12.2022
Project Composition of the SFB 876
The collaborative research center is divided into multiple projects. An extensive overview of all projects and their main objective can be found on the homepage of the SFB 876.
The Communication Networks Institute attends projects A4 and B4
News
Excellent wireless localization technology - CNI team wins IPIN competition
The CNI team (Janis Tiemann, Fabian Eckermann and Christian Wietfeld) won first prize in the "Indoor Mobile Robot Localization" category within the…
ComNets-Awards for Graduates of the Institute
The coveted awards by the "Verein der Freunde und Förderer der ComNets-Einrichtungen", who dedicated themselves to the research on future…
Collaborative Research Center with CNI-Participation Approved for 4 More Years
In the Collaborative Research Center 876 (SFB 876), the combination of data analysis (Data Mining/Big Data) with networked, embedded systems…
Successful Completion of Björn Dusza's Doctoral Studies in the Collaborative Research Center 876
Due to strongly increasing data traffic in mobile communications, the influence of the intensive use of mobile services on the battery life of…
Publications
Simulating hybrid aerial- and ground-based vehicular networks with ns-3 and LIMoSim
B. Sliwa, M. Patchou, K. Heimann, C. Wietfeld
In Proceedings of the 2020 Workshop on Ns-3, Gaithersburg, Maryland, USA, June 2020
Data-Driven Model-Predictive Communication for Resource-Efficient IoT Networks
C. Arendt, S. Böcker, C. Wietfeld
In 2020 IEEE 6th World Forum on Internet of Things (WF-IoT), April 2020
LIMITS: Lightweight machine learning for IoT systems with resource limitations
B. Sliwa, N. Piatkowski, C. Wietfeld
In 2020 IEEE International Conference on Communications (ICC), Dublin, Ireland, June 2020. (Best Paper Award)
A reinforcement learning approach for efficient opportunistic vehicle-to-cloud data transfer
B. Sliwa, C. Wietfeld
In 2020 IEEE Wireless Communications and Networking Conference (WCNC), Seoul, South Korea, May 2020
Cross-Bearing based Positioning as a Feature of 5G Millimeter Wave Beam Alignment
K. Heimann, J. Tiemann, S. Böcker, C. Wietfeld
In IEEE 91st Vehicular Technology Conference (VTC-Spring), Antwerp, Belgium, May 2020
Reliable Long-Range Multi-Link Communication for Unmanned Search and Rescue Aircraft Systems in Beyond Visual Line of Sight Operation
J. Güldenring, P. Gorczak, F. Eckermann, M. Patchou, J. Tiemann, F. Kurtz, C. Wietfeld
In Drones, MDPI, vol. 4, no. 2, May 2020
6G White Paper on Machine Learning in Wireless Communication Networks
S. Ali, et al.
In 6G Research Visions, University of Oulu, April 2020
The channel as a traffic sensor: Vehicle detection and classification based on radio fingerprinting
B. Sliwa, N. Piatkowski, C. Wietfeld
In IEEE Internet of Things Journal, March 2020
Towards cooperative data rate prediction for future mobile and vehicular 6G networks
B. Sliwa, R. Falkenberg, C. Wietfeld
In 2nd 6G Wireless Summit (6G SUMMIT), Levi, Finland, March 2020