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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

Adaptive Learning for Symbol Detection
Citation key AwanBoo2020
Author D. A. Awan, R.L.G. Cavalcante, M. Yukawa and S. Stanczak
Title of Book Machine Learning for Future Wireless Communications
Pages 15
Year 2020
DOI 10.1002/9781119562306.ch11
Location New York, United States
Month December
Editor Wiley & IEEE Press
Publisher Wiley & IEEE Press
Chapter 11
Abstract This chapter introduces a novel machine learning algorithm for symbol detection in multiuser environments. It considers a challenging multiuser uplink scenario in which the number of antennas available at the base station may be smaller than the number of active users. More specifically, the proposed method is an adaptive (nonlinear) receive filter that learns to detect symbols from data directly, without performing any intermediate estimation tasks (e.g. channel estimation). Furthermore, the method is robust against abrupt changes of the wireless environment. The proposed algorithms for symbol detection are based on the theory of reproducing kernel Hilbert spaces, which have been extensively used in diverse fields such as statistics, probability, signal processing, and machine learning, among others. It also discusses the adaptive learning method for symbol detection in multiuser environments.
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Journal Publications

D. A. Awan, Renato L.G. Cavalcante and Slawomir Stanczak (2020). Robust Cell-Load Learning with a Small Sample Set. IEEE Transactions on Signal Processing (TSP), 68:270-283.

Cheng-Xiang Wang, Marco Di Renzo, Slawomir Stanczak, Sen Wang, Erik G. Larsson (2020). Artificial Intelligence Enabled Wireless Networking for 5G and Beyond: Recent Advances and Future Challenges. IEEE Wireless Communications Magazine, February 2020/Intelligent Radio: When Artificial Intelligence Meets Radio Network

R. L.G. Cavalcante, Q. Liao and S. Stanczak (2019). Connections between spectral properties of asymptotic mappings and solutions to wireless network problems. IEEE Transactions on Signal Processing, Feb. 2019 (accepted)

S. Limmer and S. Stanczak (2018). A Neural Architecture for Bayesian Compressive Sensing over the Simplex via Laplace Techniques. IEEE Trans. on Signal Processing, 66(22):6002-6015, Nov. 2018.

C. Bockelmann, N. Pratas, G. Wunder, S. Saur, M. Navorro, D. Gregoratti, G. Vivier, E. de Carvalho, Y. Ji, C. Stefanovic, P. Popovski, Q. Wang, M. Schellmann, E. Kosmatos, P. Demestichas, M. Raceala-Motoc, P. Jung, S. Stanczak and A. Dekorsy (2018). Towards Massive Connectivity Support for Scalable mMTC Communications in 5G networks. IEEE Access (Volume: 6), pages 28969 - 28992, May 16, 2018

J. Schreck and P. Jung and S. Stanczak (2018). Compressive Rate Estimation with Applications to Device-to-Device Communications. IEEE Transactions on Wireless Communications

W. Samek and S. Stanczak and T. Wiegand (2017). The Convergence of Machine Learning and Communications. ITU Journal: ICT Discoveries, Special Issue No. 1

R.L.G. Cavalcante and M. Kasparick and S. Stanczak (2017). Max-Min Utility Optimization in Load Coupled Interference Networks. IEEE Transactions on Wireless Communications, vol. 16, no. 2, pp. 705-716, Feb. 2017

J. Mohammadi and S. Limmer and S. Stanczak (2016). A Decentralized Eigenvalue Computation Method for Spectrum Sensing Based on Average Consensus. Frequenz, July 2016

R.L.G. Cavalcante and S. Stanczak and J. Zhang and H. Zhuang (2016). Low complexity iterative algorithms for power estimation in ultra-dense load coupled networks. IEEE Trans. Signal Processing, vol. 64, no. 22, pp. 6058-6070, Nov. 2016

R.L.G. Cavalcante and Y. Shen and S. Stanczak (2016). Elementary Properties of Positive Concave Mappings With Applications to Network Planning and Optimization. IEEE Trans. Signal Processing, vol. 64, no. 7, pp. 1774-1783, April 2016

E. Pollakis and R.L.G. Cavalcante and S. Stanczak (2016). Traffic Demand-Aware Topology Control for Enhanced Energy-Efficiency of Cellular Networks. EURASIP Journal on Wireless Communications and Networks, vol. 2016, no. 1, pp. 1-17, Feb. 2016

G. Cao and P. Jung and S. Stanczak and F. Yu (2016). Data Aggregation and Recovery in Wireless Sensor Networks Using Compressed Sensing. International Journal of Sensor Networks (IJSNet), 209-219.

M. Kasparick and R. L. G. Cavalcante and S. Valentin and S. Stanczak and M. Yukawa (2015). Kernel-Based Adaptive Online Reconstruction of Coverage Maps With Side Information. IEEE Transactions on Vehicular Technology, vol. 65, no. 7, pp. 5461-5473, July 2016 (also available at http://arxiv.org/abs/1404.0979)

S. Maghsudi and S. Stanczak (2015). Hybrid Centralized-Distributed Resource Allocation for Device-to-Device Communication Underlaying Cellular Networks. IEEE Trans. Veh. Technol., 2481-2495.

M. Goldenbaum and H. Boche and S. Stanczak (2015). Nomographic Functions: Efficient Computation in Clustered Gaussian Sensor Networks. IEEE Trans. Wireless Commun., 2093–2105.

S. Maghsudi and S. Stanczak (2015). Channel Selection for Network-Assisted D2D Communication via No-Regret Bandit Learning With Calibrated Forecasting. IEEE Transactions on Wireless Communications, 1309-1322.

F. Penna and S. Stanczak (2015). Decentralized Eigenvalue Algorithms for Distributed Signal Detection in Cognitive Networks. IEEE Transactions on Signal Processing, 63(2):427-440, Jan. 2015

R. Cavalcante and S. Stanczak and M. Schubert and A. Eisenblätter and U. Türke (2014). Toward Energy-Efficient 5G Wireless Communications Technologies. IEEE Signal Processing Magazine, vol. 31, no. 6, pp. 24-34, Nov. 2014

M. Goldenbaum and S. Stanczak (2014). On the Channel Estimation Effort for Analog Computation Over Wireless Multiple-Access Channels. IEEE Wireless Communications Letters, 261-264.

G. Cao and P. Jung and S. Stanczak (2014). Low Cost Error Correction for Multi-hop Data Aggregation Using Compressed Sensing. IEICE Trans. on Information and System

A. Giovanidis and Q. Liao and S. Stanczak (2014). Measurement-Adaptive Cellular Random Access Protocols. Wireless Networks. Springer Verlag (Germany), 1495-1514.

M. Goldenbaum and H. Boche and S. Stanczak (2013). Harnessing Interference for Analog Function Computation in Wireless Sensor Networks. IEEE Transactions on Signal Processing, 4893–4906.

M. Goldenbaum and S. Stanczak (2013). Robust Analog Function Computation via Wireless Sensor Multiple-Access Channels. IEEE Transactions on Communications, 3863-3877.

M. Zheng and P. Pawelczak and S. Stanczak and H. Yu (2013). Planning of Cellular Networks Enhanced by Energy Harvesting. IEEE Communications Letters, 1092–1095.

R.L.G. Cavalcante and S. Stanczak (2013). A Distributed Subgradient Method for Dynamic Convex Optimization Problems under Noisy Information Exchange. IEEE Journal of Selected Topics in Signal Processing, vol. 7, no. 2, pp. 243-256, April 2013

I. Koutsopoulos and S. Stanczak (2012). The Impact of Transmit Rate Control on Energy-efficient Estimation in Wireless Sensor Networks. IEEE Trans. Wireless Commun., 3261–3271.

A. Giovanidis and S. Stanczak (2011). Stability and Distributed Power Control in MANETs with Per Hop Retransmissions. IEEE Transactions on Communications, 1632 -1643.

S. Stanczak and M. Kaliszan and N. Bambos (2010). A Characterization of Max-Min SIR-Balanced Power Allocation with Applications. Wireless Networks (Springer), 2335–2347.

S. Stanczak and A. Feistel and M. Wiczanowski and H. Boche (2010). Utility-based Power Control with QoS Support. Wireless Networks (Springer), 1691–1705.

A. Feistel and S. Stanczak and D. Tomecki (2010). Joint Utility-Based Power Control and Receive Beamforming in Decentralized Wireless Networks. EURASIP Journal on Wireless Communications and Networking.

S. Stanczak and M. Kaliszan and N. Bambos (2010). Decentralized Admission Control for Power-Controlled Wireless Links. CoRR

M. Wiczanowski and H. Boche and S. Stanczak (2009). An Algorithm for Optimal Resource Allocation in Cellular Networks with Elastic Traffic. IEEE Transactions on Communications, 41–44.

H. Boche and S. Stanczak (2008). Strict Convexity of the Log-SIR region. IEEE Transactions on Communications, 1511–1518.

M. Wiczanowski and S. Stanczak and H. Boche (2008). Performance and Interference Control in Wireless Ad hoc and Mesh Networks— A Generalized Lagrangian Approach. IEEE Transactions on Signal Processing, 4039–4052.

M. Wiczanowski and S. Stanczak and H. Boche (2008). Providing Quadratic Convergence of Decentralized Power Control in Wireless Networks—The Method of Min-Max Functions. IEEE Transactions on Signal Processing, 4053–4068.

H. Boche and M. Wiczanowski and S. Stanczak (2008). On Optimal Resource Allocation in Cellular Networks with Best-Effort Traffic. IEEE Transactions on Wireless Communications, 1163–1167.

S. Stanczak and M. Wiczanowski and H. Boche (2007). Distributed Utility-Based Power Control: Objectives and Algorithms. IEEE Trans. Signal Processing, 5058–5068.

H. Boche and S. Stanczak (2007). A Note on Some Properties of the Perron Root of Nonnegative Irreducible Matrices. Appl. Alg. Eng. Comm. Comp., 369–378.

S. Stanczak and H. Boche (2007). On the Convexity of Feasible QoS Regions. IEEE Transactions on Information Theory, 779-783.

H. Boche and M. Wiczanowski and S. Stanczak (2007). Unifying View on Min-Max Fairness, Max-Min Fairness, and Utility Optimization in Cellular Networks. EURASIP J. Wireless Commun. and Net.

H. Boche and S. Stanczak (2006). The Kullback–Leibler Divergence and Nonnegative Matrices. IEEE Transactions on Information Theory, 5539-5545.

S. Stanczak and H. Boche (2006). The Infeasible SIR Region Is Not a Convex Set. IEEE Transactions on Communications, 1905-1907.

S. Stanczak and G. Wunder and H. Boche (2006). On Pilot-based Multipath Channel Estimation for Uplink CDMA Systems: An Overloaded Case. IEEE Trans. Signal Processing, 512-519.

H. Boche and S. Stanczak (2005). Log-Convexity of the Minimum Total Power in CDMA Systems with Certain Quality-Of-Service Guaranteed. IEEE Transactions on Information Theory, 374-381.

H. Boche and S. Stanczak (2004). Convexity of Some Feasible QoS Regions and Asymptotic Behavior of the Minimum Total Power in CDMA Systems. IEEE Transactions on Communications, 2190-2197.

H. Boche and S. Stanczak (2004). On Systems of Linear Equations with Nonnegative Coefficients. Appl. Alg. Eng. Comm. Comp., 397-414.

H. Boche and S. Stanczak (2003). Optimal allocation of resources in an asynchronous CDMA channel with identical SINR requirements for all users. IEICE Trans. on Communications, 397-405.

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
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