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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. Prof. Stanczak 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. He was an Associate Editor of the IEEE Transactions on Signal Processing between 2012 and 2015. Since February 2018 Prof. Stanczak has been the chairman of the ITU-T focus group on machine learning for future networks including 5G.
Teaching
- 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)
- 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)
- Winter 2018/19
- VL Fundamentals of Digital Wireless Communication (Prof. Dr.-Ing. Slawomir Stanczak)
- VL Mathematical Introduction to Machine Learning (Dr. rer. nat. Igor Bjelakovic)
- Summer 2018
- VL Mathematical Methods in Signal Processing and Communications (Prof. Dr.-Ing. S.Stanczak)
- VL Modern Signal Processing for Communications (Dr. R. Cavalcante)
- Winter 2017/18
- VL Fundamentals of Digital Wireless Communication
- VL Selected topics in Wireless Network Optimization
- Summer 2017
- VL Mathematical Methods in Signal Processing and Communications
- VL Modern Signal Processing for Communications
- Winter 2016/17
- VL Fundamentals of Digital Wireless Communication
- VL Selected topics in Wireless Network Optimization
- Summer 2016
- VL Wireless Network Analysis and Optimization
- VL Modern Signal Processing for Communications
- Winter 2015/16
- VL Mathematical Methods in Signal Processing and Communications
- SE Selected Topics in Wireless Network Optimization
- Summer 2015
- VL Cross-Layer Optimization and Resource Allocation in Wireless Networks
- Winter 2014/15
- VL Foundations of Digital and Wireless Communication
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Conference, Symposium, and Workshop Papers
| Citation key | pfad2020gc |
|---|---|
| Author | A. Pfadler, P. Jung and S. Stanczak |
| Year | 2020 |
| Journal | IEEE Globecom 2020, December 7-11, in Taipei, Taiwan |
| Month | Dec |
| Editor | IEEE |
| Abstract | Orthogonal time frequency and space (OTFS) modulation is a pulse-shaped Gabor signaling scheme with additional time-frequency (TF) spreading using the symplectic finite Fourier transform (SFFT). With sufficient accurate channel information and sophisticated equalizers it promises performance gains in terms of robustness for high mobility users. To fully exploit diversity in OTFS, the 2D-deconvolution implemented by a linear equalizer should approximately invert the doubly dispersive channel operation, which however is a twisted convolution. In theory, this is achieved in a first step by matching the TF grid and the Gabor synthesis and analysis pulses to the delay and Doppler spread of the channel. However, in practice, one always has to balance between supporting high granularity in delay-Doppler (DD) spread, and multi-user and network aspects. In this paper, we propose mobility modes with distinct grid and pulse matching for different doubly dispersive channel. To account for remaining self-interference, we tune the minimum mean square error (MMSE) linear equalizer without the need of estimating channel cross talk coefficients. We evaluate our approach with the QuaDRiGa channel simulator and with OTFS transceiver architecture based on a polyphase implementation for orthogonalized Gaussian pulses. In addition, we compare OTFS to a IEEE 802.11p compliant design of cyclic prefix (CP) based orthogonal frequency-division multiplexing (OFDM). Our results indicate that with an appropriate mobility mode, the potential OTFS gains can be indeed achieved with linear equalizers to significantly outperforms OFDM. |
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Head of Chair
Prof. Dr.-Ing. Slawomir StanczakHFT 400a
Einsteinufer 25
10587 Berlin
Tel.: +49(0)30 314-28465
Fax: +49(0)30 314-28320
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