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
tinyLTE: Lightweight, Ad Hoc Deployable Cellular Network for Vehicular Communication
F. Eckermann, P. Gorczak, C. Wietfeld,
In IEEE Vehicular Technology Conference (VTC-Spring), June 2018.
Efficient Machine-type Communication using Multi-metric Context-awareness for Cars used as Mobile Sensors in Upcoming 5G Networks
B. Sliwa, T. Liebig, R. Falkenberg, J. Pillmann, C. Wietfeld,
In IEEE Vehicular Technology Conference (VTC-Spring), Porto, Portugal, June 2018.
Enhanced UAV Indoor Navigation through SLAM-Augmented UWB Localization
J. Tiemann, A. Ramsey, C. Wietfeld,
In IEEE International Conference on Communications Workshops (ICC Workshops), Kansas City, USA, May 2018.
System-in-the-loop Design Space Exploration for Efficient Communication in Large-scale IoT-based Warehouse Systems
R. Falkenberg, J. Drenhaus, B. Sliwa, C. Wietfeld,
In 2018 Annual IEEE International Systems Conference (SysCon), IEEE, Vancouver, Canada, April…
A Radio-fingerprinting-based Vehicle Classification System for Intelligent Traffic Control in Smart Cities
B. Sliwa, M. Haferkamp, M. Al-Askary, C. Wietfeld,
In 2018 Annual IEEE International Systems Conference (SysCon), IEEE, Vancouver, Canada, April…
On the Potential of 5G mmWave Pencil Beam Antennas for UAV Communications: An Experimental Evaluation
K. Heimann, J. Tiemann, S. Böcker, C. Wietfeld,
In 22nd International ITG Workshop on Smart Antennas, VDE Verlag GMBH Berlin und Offenbach, Mach…
The Radio Field as a Sensor - a Segmentation Based Soil Moisture Sensing Approach
F. Liedmann, C. Holewa, C. Wietfeld,
In 2018 IEEE Sensors Applications Symposium, Seoul, Korea, March 2018.
Machine Learning Based Indoor Localisation Using Environmental Data in PhyNetLab Warehouse
M. Masoudinejad, et al.,
In Smart SysTech 2018; European Conference on Smart Objects, Systems and Technologies, VDE, pp. 1–8, 2018.
Discover Your Competition in LTE: Client-Based Passive Data Rate Prediction by Machine Learning
R. Falkenberg, K. Heimann, C. Wietfeld,
In 2017 IEEE Global Communications Conference (GLOBECOM), Singapore, pp. 1–7, December 2017.