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Prof. Dr.-Ing. Slawomir Stanczak
- © TU Berlin/Pressestelle/Philipp Arnoldt
Slawomir Stanczak studied electrical engineering with specialization in control theory at the Wroclaw University of Technology and at the Technical University of Berlin (TU Berlin). He received the Dipl.-Ing. degree in 1998 and the Dr.-Ing. degree (summa cum laude) in electrical engineering in 2003, both from TU Berlin; the Habilitation degree (venialegendi) followed in 2006. Since 2015, he has been a Full Professor for network information theory with TU Berlin and the head of the Wireless Communications and Networks department at Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute (HHI). Prof. Stanczak has been involved in research and development activities in wireless communications since 1997. In 2004 and 2007, he was a Visiting Professor with RWTH Aachen University and in 2008, he was a Visiting Scientist with Stanford University, Stanford, CA, USA. He is a co-author of two books and more than 200 peer-reviewed journal articles and conference papers in the area of information theory, wireless communications, signal processing and machine learning. Prof. Stanczak received research fellowships from the German Research Foundation and the Best Paper Award from the German Communication Engineering Society in 2014. He was a Co-chair of the 14th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2013). Between 2009 and 2011, he was an Associate Editor of the European Transactions for Telecommunications (information theory) and an Associate Editor of the IEEE Transactions on Signal Processing between 2012 - 2015 and the chair of the ITU-T Focus Group on Machine Learning for Future Networks including 5G from 2017 - 2020. Since 2020, Prof. Stanczak is chairman of the 5G BERLIN association and since 2021 he is coordinator of the 6G-RIC (Research & Innovation Cluster).
Teaching
- Summer 2022
- VL Theory and Algorithms of Machine Learning (Prof. Dr.-Ing. Slawomir Stanczak)
- VL Modern Signal Processing and Communications (Dr. Renato L.G. Cavalcante)
- VL Selected Topics in Wireless Communications and Networking (Dr. Zoran Utkovski)
- Master Project Network Information Systems (Dr.- Ing. Julius Schulz- Zander)
- Winter 2021/22
- VL Fundamentals of Digital Wireless Communication (Prof. Dr.-Ing. Slawomir Stanczak)
- VL Mathematical Introduction to Machine Learning (Dr. rer. nat. Igor Bjelakovic)
- Summer 2021
- VL Theory and Algorithms of Machine Learning (Prof. Dr.-Ing. Slawomir Stanczak)
- VL Modern Signal Processing and Communications (Dr. Renato L.G. Cavalcante)
- VL Selected Topics in Wireless Communications and Networking (Dr. Zoran Utkovski)
- Master Project Network Information Systems (Dr.- Ing. Julius Schulz- Zander)
- Winter 2020/21
- VL Fundamentals of Digital Wireless Communication (Prof. Dr.-Ing. Slawomir Stanczak)
- VL Mathematical Introduction to Machine Learning (Dr. rer. nat. Igor Bjelakovic)
- VL Introduction to Game Theory with Engineering Applications (Prof. Dr.-Ing. Setareh Maghsudi)
- Summer 2020
- VL Theory and Algorithms of Machine Learning (Prof. Dr.-Ing. Slawomir Stanczak)
- VL Modern Signal Processing and Communications (Dr. Renato L.G. Cavalcante)
- VL Selected Topics in Wireless Communications and Networking (Dr. Zoran Utkovski)
- Winter 2019/20
- VL Fundamentals of Digital Wireless Communication (Prof. Dr.-Ing. Slawomir Stanczak)
- VL Mathematical Introduction to Machine Learning (Dr. rer. nat. Igor Bjelakovic)
- Summer 2019
- VL Theory and Algorithms of Machine Learning (Prof. Dr.-Ing. Slawomir Stanczak)
- VL Modern Signal Processing and Communications (Dr. Renato L.G. Cavalcante)
- VL Selected Topics in Wireless Communications and Networking (Dr. Zoran Utkovski)
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Preprints
| Zitatschlüssel | Joint2016 |
|---|---|
| Autor | Q. Liao and D. A. Awan and S. Stanczak |
| Jahr | 2016 |
| Journal | Preprint available at: arXiv:1607.04754, 8 pages, 6 figures |
| Zusammenfassung | This paper develops an optimization framework for self-organizing networks (SON). The objective is to ensure efficient network operation by a joint optimization of different SON functionalities, which includes capacity, coverage and load balancing. Based on the axiomatic framework of monotone and strictly subhomogeneous function, we formulate an optimization problem for the uplink and propose a two-step optimization scheme using fixed point iterations: i) per base station antenna tilt optimization and power allocation, and ii) cluster-based base station assignment of users and power allocation. We then consider the downlink, which is more difficult to handle due to coupled variables, and show downlink-uplink duality relationship. As a result, a solution for the downlink is obtained by solving the uplink problem. Simulations show that our approach achieves a good trade-off between coverage, capacity and load balancing. |