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
10/10/2019
Four publications addressing recent topics in automotive communication networks presented at IEEE VTC-Fall 2019
Key results of the vehicular research projects "SFB 876 (B4): Analysis and Communication for Dynamic Traffic Prognosis" and "Intelligente…
10/10/2019
Workshop Series on "Resource constraints in data science - Recent research results and future directions within the SFB 876"
The SFB 876 has kicked off a series of workshops with dedicated themes about recent advancements in data science, artificial intelligence and adjacent…
09/11/2018
IEEE Student Fellowship for Outstanding Contributions to Machine Learning in Communications based on research in DFG SFB 876
We are very happy to announce that Benjamin Sliwa has received the 2018 Transportation Electronics Fellowship Award "For Outstanding Student Research…
04/07/2017
Bernhard-Walke Dissertationspreis for CNI-Alumnus Niklas Goddemeier
This year, the award, that includes prize money of 1,500 euros, for the best Ph.D. thesis of all Communication Networks Institutes of the "Freunde und…
04/06/2017
5G-Initiative for Germany - TU Dortmund Is a Part of It
5G-Initiative for Germany - TU Dortmund is a part of it: The Federal Minister for Traffic and Digital Infrastructure has started an initiative, that…
12/06/2016
Awards for Staff Members of the Institute
At the end of 2016, we are delighted that two scientists of the institute have been honored with notable awards for their research. Dr.-Ing. Christoph…
Publications
12/31/2022
Vehicle to Vehicle Communications: Machine Learning-Enabled Predictive Routing
C. Krieger, B. Sliwa, C. Wietfeld
In Volume 3 Machine Learning under Resource Constraints - Applications, De Gruyter, December 2022.
12/31/2022
Potential of Millimeter Wave Communications
K. Heimann, S. Häger, C. Wietfeld
In Volume 3 Machine Learning under Resource Constraints - Applications, De Gruyter, December 2022.
10/12/2022
3D Self-Motion Tracking Services: Coalescence of mmWave Beam Orientations and Phase Information
S. Häger, S. Böcker, C. Wietfeld
In 2022 IEEE Future Networks World Forum (FNWF), Montreal, Canada, October 2022.
10/12/2022
TinyDRaGon: Lightweight Radio Channel Estimation for 6G Pervasive Intelligence
M. Geis, B. Sliwa, C. Bektas, C. Wietfeld
In 2022 IEEE Future Networks World Forum (FNWF), October 2022.
06/22/2022
From LENA to LENA-NB: Implementation and Performance Evaluation of NB-IoT and Early Data Transmission in ns-3
P. Jörke, T. Gebauer, C. Wietfeld
In Workshop on ns-3 (WNS3), Online, Juni 2022.
06/19/2022
Scaling Dense NB-IoT Networks to the Max: Performance Benefits of Early Data Transmission
P. Jörke and T. Gebauer, S. Böcker, C. Wietfeld
In 2022 IEEE 95th Vehicular Technology Conference: VTC2022-Spring.
04/25/2022
System Modeling and Performance Evaluation of Predictive QoS for Future Tele-Operated Driving
H. Schippers, C. Schüler, B. Sliwa, C. Wietfeld
In 2022 Annual IEEE International Systems Conference (SysCon), Virtual Event.
04/25/2022
QoE Evaluation of Real-Time Remote Operation with Network Constraints in a System-of-Systems
C. Schüler, T. Gebauer, M. Patchou, C. Wietfeld
In 2022 Annual IEEE International Systems Conference (SysCon), Virtual Event.
04/13/2022
DRaGon: Mining latent radio channel information from geographical data leveraging deep learning
B. Sliwa, M. Geis, C. Bektas, M. Lopéz, P. Mogensen, C. Wietfeld
In 2022 IEEE Wireless Communications and Networking Conference (WCNC), Austin, Texas