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Prof. Dr.-Ing. Slawomir Stanczak

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© 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 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

 

You can also find me on:

Fraunhofer Heinrich-Hertz-Institut

Google Scholar

arXiv

LinkedIn


Publications

Books

S. Stanczak and M. Wiczanowski and H. Boche (2009). Fundamentals of Resource Allocation in Wireless Networks. volume 3 of Foundations in Signal Processing, Communications and Networking. Springer, Berlin, 2009. Springer, Berlin.

S. Stanczak and M. Wiczanowski and H. Boche (2006). Resource Allocation in Wireless Networks - Theory and Algorithms. Lecture Notes in Computer Science (LNCS 4000). Springer, Berlin, 2006. Springer, Berlin.

Book Chapters

D. A. Awan, R.L.G. Cavalcante, M. Yukawa and S. Stanczak (2020). Adaptive Learning for Symbol Detection. Machine Learning for Future Wireless Communications. Wiley & IEEE Press, 15.

S. Maghsudi and S. Stanczak (2015). Communications in Interference-Limited Networks. chapter Distributed Channel Selection for Underlay Device-to-Device Communications: A Game- Theoretical Learning Framework. Springer International Publishing, 2015. Springer International Publishing.

M. Goldenbaum and S. Stanczak and H. Boche (2015). Communications in Interference-Limited Networks. chapter Interference-Aware Analog Computation over the Wireless Channel: Fundamentals and Strategies. Springer International Publishing, 2015. Springer International Publishing.

R. L. G. Cavalcante and S. Stanczak and I. Yamada (2014). Cooperative Cognitive Radios with Diffusion Networks. chapter Cognitive Radio and Sharing Unlicensed Spectrum in the book Mechanisms and Games for Dynamic Spectrum Allocation, pages 262{303. Cambridge University Press, UK, 2014, 262–303.

S. Stanczak and H. Boche (2005). Towards a better understanding of the QoS tradeoff in multiuser multiple antenna systems. Smart Antennas–State-of-the-Art. Hindawi Publishing Corporation, 521-543.

Journal Publications

Robust Cell-Load Learning with a Small Sample Set
Citation key Robawan2019
Author D. A. Awan, Renato L.G. Cavalcante and Slawomir Stanczak
Pages 68:270-283
Year 2020
DOI 10.1109/TSP.2019.2959221
Journal IEEE Transactions on Signal Processing (TSP)
Volume 68
Number 68
Month Jan.
Abstract Learning of the cell-load in radio access networks (RANs) has to be performed within a short time period. Therefore, we propose a learning framework that is robust against uncertainties resulting from the need for learning based on a relatively small training set. To this end, we incorporate prior knowledge about the cell-load in the learning framework. For example, an inherent property of the cell-load is that it is monotonic in downlink (data) rates. To obtain additional prior knowledge we first study the feasible rate region, i.e., the set of all vectors of user rates that can be supported by the network. We prove that the feasible rate region is compact. Moreover, we show the existence of a Lipschitz function that maps feasible rate vectors to cell-load vectors. With these results in hand, we present a learning technique that guarantees a minimum approximation error in the worst-case scenario by using prior knowledge and a small training sample set. Simulations in the network simulator NS3 demonstrate that the proposed method exhibits better robustness and accuracy than standard learning techniques, especially for small training sample sets.
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Conference, Symposium, and Workshop Papers

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M. A. Gutierrez-Estevez, Z. Utkovski, P. Agostini, D. Schäufele, M. Frey, I. Bjelakovic and S. Stanczak (2020). Quality-of-Service prediction for physical-layer security via secrecy maps. 45th International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 in Barcelona, Spain, May 4-8 2020

R. L. G. Cavalcante, Q. Liao and S. Stanczak (2020). Connections between spectral properties of asymptotic mappings and solutions to wireless network problems. accepted, 45th International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 in Barcelona, Spain, May 4-8 2020

R. L. G. Cavalcante and S. Stanczak (2020). Channel covariance estimation in multiuser massive MIMO systems with an approach based on infinite dimensional hilbert spaces. accepted, 45th International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 in Barcelona, Spain, May 4-8 2020

J. Dommel, Z. Utkovski, S. Stanczak and O. Simeone (2020). Joint source-channel coding and bayesian message passing detection for grant-free radio access in IOT. 45th International Conference on Acoustics, Speech, and Signal Processing, (to appear), Barcelona, Spain, May 4-8 2020

M. Mehlhose, D. A. Awan, R. L.G. Cavalcante, M. Kurras and S. Stanczak (2020). Machine Learning-Based Adaptive Receive Filtering: Proof-of-Concept on an SDR Platform. accepted, IEEE International Conference on Communications (ICC), Dublin, Ireland, 2020

J. Fink, M. Kasparick and S. Stanczak (2020). Robust Submodular RRH Selection for Joint Multicast Downlink Transmission. 24th International ITG Workshop on Smart Antennas (WSA 2020), Hamburg, Germany, 18-20 Feb. 2020, (to appear)

J. Fink, R. L.G. Cavalcante and S. Stanczak (2020). Online Channel Estimation for Hybrid Beamforming Architectures. International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), 4-8 May 2020, Barcelona, Spain (to appear)

A. Pfadler, P. Jung and S. Stanczak (2020). Pulse-Shaped OTFS for V2X Short-Frame Communication with Tuned One-Tap Equalization. 24th International ITG Workshop on Smart Antennas, Poster presentation, February 18-20, 2020 in Hamburg, Germany

M. Mehlhose, D. A. Awan, R. L.G. Cavalcante, M. Kurras, S. Stanczak (2020). Machine Learning-Based Adaptive Receive Filtering: Proof-of-Concept on an SDR Platform. 45th International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020, May 4-8, 2020, Barcelona, Spain (accepted demo submission)

R. L. G. Cavalcante and S. Stanczak (2020). A hybrid model-data driven approach for the estimation of the angular power spectrum in massive MIMO systems. IEEE Statistical Signal Processing Workshop 2020, Rio de Janeiro, Brazil, 12th-15th July, 2020 (to appear)

J. Dommel, Z. Utkovski, O. Simeone and S. Stanczak (2020). Joint Source-Channel Coding for Grant-Free Radio Access in IoT Fog Networks: Edge vs Cloud Processing. IEEE Statistical Signal Processing Workshop 2020, Rio de Janeiro, Brazil, 12th-15th July, 2020 (to appear)

R. Hernangómez and A. Santra and S. Stanczak (2019). Human Activity Classification with Frequency Modulated Continuous Wave Radar Using Deep Convolutional Neural Networks. RADAR 2019 International Conference, 23-27 Sept. 2019, Toulon, France

I. Bjelakovic, M. Frey and S. Stanczak (2019). Distributed Approximation of Functions over Fast Fading Channels with Applications to Distributed Learning and the Max-Consensus Problem. 57th Annual Allerton Conference on Communication, Control, and Computing, 24-27 Sept. 2019 in Urbana, IL, USA

J. Fink and D. Schäufele and M. Kasparick and R. L.G. Cavalcante and S. Stanczak (2019). Cooperative localization by set-theoretic estimation. 23rd International ITG Workshop on Smart Antennas (WSA), April 24-26, 2019 in Vienna, Austria

Ramya Panthangi Manjunath and Mate Boban and Chan Zhou and Slawomir Stanczak (2019). Using Learning Methods for V2V Path Loss Prediction. Phy & Fundamentals of the IEEE WCNC 2019 conference, in Marrakech, Morocco, April 15-18

Renato L.G. Cavalcante and Slawomir Stanczak (2019). Weakly standard interference mappings: existence of fixed points and applications to power control in wireless networks. International Conference on Acoustics, Speech, and Signal Processing, 12 - 17 May, 2019 in Brighton, UK

J. Fink and R. L.G. Cavalcante and S. Stanczak (2019). Multicast beamforming using semidefinite reflaxation and bounded perturbation resilience. International Conference on Acoustics, Speech and Signal Processing (ICASSP), 12 - 17 May, 2019 in Brighton, UK

N. Agrawal, M. Frey and S. Stanczak (2019). A Scalable Max-Consensus Protocol For Noisy Ultra-Dense Networks. IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2-5 July 2019, Cannes, France

Z. Utkovski, P. Agostini, M. Frey, I. Bjelakovic and S. Stanczak (2019). Learning Radio Maps for Physical-Layer Security in the Radio Access. IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2-5 July 2019, Cannes, France

D. Schäufele, R. L.G. Cavalcante and S. Stanczak (2019). Tensor Completion for Radio Map Reconstruction using Low Rank and Smoothness. IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

R. Panthangi Manjunath, M. Boban, C. Zhou and S. Stanczak (2019). Online Learning Framework for V2V Link Quality Prediction. IEEE GLOBECOM 2019, December 9 – 13, in Waikoloa, Hawaii, USA

J. Dommel, Z. Utkovski, L. Thiele and S. Stanczak (2019). Sparse Code-Domain Non-Orthogonal Random Access with Turbo-Peeling Decoder. Asilomar Conference on Signals, Systems, and Computers (Nov 3-6, 2019) in Pacific Grove, CA, USA

M. Frey and I. Bjelakovic and S. Stanczak (2018). Resolvability on Continuous Alphabets. IEEE International Symposium on Information Theory (ISIT)

J. Fink and R. L.G. Cavalcante and P. Jung and S. Stanczak (2018). Extrapolated Projection Methods for PAPR Reduction. 26th European Signal Processing Conference (EUSIPCO 2018), Sept. 2018

D. A. Awan and R.L.G. Cavalcante and M. Yukawa and S. Stanczak (2018). Detection for 5G-NOMA: An Online Adaptive Machine Learning Approach. IEEE International Conference on Communications (ICC), Kansas City, MO, USA.

L. Miretti and R.L.G. Cavalcante and S. Stanczak (2018). FDD massive MIMO channel spatial covariance conversion using projection methods. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

D. A. Awan and R.L.G. Cavalcante and S. Stanczak (2018). A Robust Machine Learning Method for Cell-Load Approximation in Wireless Networks. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Calgary, Alberta, Canada.

R. L. G. Cavalcante and L. Miretti and S. Stanczak (2018). Error Bounds for FDD Massive MIMO Channel Covariance Conversion with Set-Theoretic Methods. Proc. IEEE Global Telecommunications Conference (GLOBECOM), Dec. 2018 (to appear)

F. Molinari and S. Stanczak and J. Raisch (2018). Exploiting the Superposition Property of Wireless Communication for Max-Consensus Problems in Multi-Agent Systems. European Control Conference, Limassol, Cyprus, June 12-15

P. Agostini and Z. Utkovski and S. Stanczak and J. Pilz (2018). Scalable massive random access in C-RAN with fronthaul limitations. 15th International Symposium on Wireless Communication Systems (ISWCS) 2018

R. L. G. Cavalcante and S. Stanczak (2018). Spectral radii of asymptotic mappings and the convergence speed of the standard fixed point algorithm. Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr. 2018

D. A. Awan, R. L.G. Cavalcante, Z. Utkovski and S. Stanczak (2018). Set-Theoretic Learning for Detection in Cell-Less C-RAN System. IEEE Global Conference on Signal and Information Processing, California, USA, Nov. 26-29, 2018

L. Miretti, R. L.G. Cavalcante and S. Stanczak (2018). Downlink channel spatial coveriance estimation in realistic FDD massive MIMO systems. 6th IEEE Global Conference on Signal and Information Processing, Anaheim, California, USA, Nov. 26-29, 2018

M.A. Gutierrez-Estevez and R.L.G. Cavalcante and S. Stanczak (2018). Nonparametric Radio Maps Reconstruction via Elastic Net Regularization with Multi-Kernels. IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

M. Raceala-Motoc and P. Jung and Z. Utkovski and S. Stanczak (2018). C-RAN-Assisted Non-Coherent Grant-Free Random Access Based on Compute-and-Forward. IEEE GLOBECOM 2018

M. Raceala-Motoc and S. Limmer and I. Bjelakovic and S. Stanczak (2018). Distributed Machine Learning in the Context of Function Computation over Wireless Networks. 52nd Asilomar Conference on Signals, Systems and Computers 2018, Preprint.

Renato L. G. Cavalcante and Slawomir Stanczak (2018). Low-complexity distributed set-theoretic decoders for analog fountain codes. 52nd Asilomar Conference on Signals, Systems and Computers 2018, Preprint.

R. L. G. Cavalcante and S. Stanczak (2017). The role of asymptotic functions in network optimization and feasibility studies. 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP), 563-567.

M. Frey and I. Bjelakovic and S. Stanczak (2017). MAC resolvability: First and second order results. 2017 IEEE Conference on Communications and Network Security (CNS), 560-564.

M. Vural and P. Jung and S. Stanczak (2017). A new outlier detection method based on anti-sparse representations. 2017 25th Signal Processing and Communications Applications Conference (SIU), 1-4.

M. Vural and P. Jung and S. Stanczak (2017). Effect of anti-sparse prior on PAPR performance analysis. 2017 25th Signal Processing and Communications Applications Conference (SIU), 1-4.

M. A. Gutierrez-Estevez and S. Stanczak (2017). Distributed Multi-Object Auctions for Energy Transfer between Harvesting Nodes. WSA 2017; 21th International ITG Workshop on Smart Antennas, 1-7.

R. L. G. Cavalcante and S. Stanczak (2017). Peak Load Minimization in Load Coupled Interference Networks. The 42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

M. Botsov and S. Stanczak and P. Fertl (2016). On the Overhead of Radio Resource Management Schemes for Mobile Underlay D2D Communication. IEEE Vehicular Networking Conference (VNC)

M. A. Gutierrez-Estevez and R. L. G. Cavalcante and S. Stanczak and J. Zhang and H. Zhuang (2016). A Distributed Solution for Proportional Fairness Optimization in Load Coupled OFDMA Networks. IEEE Global Conference on Signal and Information Processing (GlobalSIP)

D. A. Awan and R. L.G. Cavalcante and S. Stanczak (2016). Distributed RAN and backhaul optimization for energy efficient wireless networks. IEEE Global Conference on Signal and Information Processing (GlobalSIP), Washington , D.C., USA.

M. Raceala-Motoc and J. Schreck and P. Jung and S. Stanczak (2016). Robust Message Recovery for Non-Cooperative Compute-and-Forward Relaying. 50th Annual Asilomar Conference on Signals, Systems, and Computers

M. Goldenbaum and P. Jung and M. Raceala-Motoc and S. Stanczak and C. Zhou (2016). Harnessing Channel Collisions to Efficiently Deal with the Massive Access in 5G Networks. 9th International Symposium on Turbo Codes & Iterative Information Processing 2016 - Workshop 5G: 5G for Internet of Things

M. A. Gutierrez-Estevez and D. Gozalvez-Serrano and M. Botsov and S. Stanczak (2016). STFDMA: A Novel Technique for Ad-Hoc V2V Networks Exploiting Radio Channels Frequency Diversity. 13th International Symposium on Wireless Communication Systems (ISWCS)

S. Limmer and S. Stanczak (2016). Towards optimal nonlinearities for sparse recovery using higher-order statistics. IEEE International Workshop on Machine Learning For Signal Processing (MLSP)

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Head of Chair

Prof. Dr.-Ing. Slawomir Stanczak
HFT 400a
Einsteinufer 25
10587 Berlin
Tel.: +49(0)30 314-28465
Fax: +49(0)30 314-28320

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