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T. Piotrowski and R. L. G. Cavalcante (2021). Fixed points of monotonic and (weakly) scalable neural networks. arXiv preprint arXiv:2106.16239

T. Piotrowski and R. L. G. Cavalcante (2021). The fixed point iteration of positive concave mappings converges geometrically if a fixed point exists. arXiv preprint arXiv:2110.11055

M. Frey, I. Bjelakovic and S. Stanczak (2020). Towards Secure Over-The-Air Computation. Submitted to Problems of Information Transmission. Preprint available at arXiv:2001.03174

C. Bockelmann and others (2018). Towards Massive Connectivity Support for Scalable mMTC Communications in 5G networks. Preprint (available at https://arxiv.org/abs/1804.01701)

R.L.G. Cavalcante and S. Stanczak (2018). Spectral radii of asymptotic mappings and the convergence speed of the standard fixed point algorithm. Preprint (available at https://arxiv.org/abs/1803.05671v1)

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

D. Schaeufele and R. L.G. Cavalcante and Z. Zhong and S. Stanczak (2018). Tensor Completion for Radio Map Reconstruction and Channel Cartography using Low Rank and Smoothness. Preprint

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.

R.L.G. Cavalcante and S. Stanczak (2018). Fundamental properties of solutions to utility maximization problems in wireless networks. arXiv:1610.01988

Y. Chang and P. Jung and C. Zhou and S. Stanczak (2016). Block Compressed Sensing Based Distributed Device Detection for M2M Communications. Preprint (available at https://arxiv.org/abs/1609.05080v1)


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

S. Stanczak and A. Keller and R.L.G. Cavalcante and N. Binder (2021). Long-term Perspectives: Machine Learning for Future Wireless Networks. Chapter 14 in: Shaping Future 6G Networks: Needs, Impacts, and Technologies. John Wiley & Sons and IEEE Press.

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

R. Freund, T. Haustein, M. Kasparick, K. Mahler, J. Schulz-Zander, L. Thiele, T. Wiegand, and R. Weiler (2018). 5G-Datentransport mit Höchstgeschwindigkeit. book chapter in R. Neugebauer (Ed.), "Digitalisierung: Schlüsseltechnologien für Wirtschaft und Gesellschaft" (pp. 89–111). Berlin, Heidelberg (2018)

G. Wunder, M. Kasparick, P. Jung, T. Wild, F. Schaich, Y. Chen, G. Fettweis, I. Gaspar, N. Michailow, M. Matthé, L. Mendes, D. Kténas, J.‐B. Doré, V. Berg, N. Cassiau, S. Pietrzyk, and M. Buczkowski (2016). New Physical‐layer Waveforms for 5G. book chapter in "Towards 5G: Applications, Requirements and Candidate Technologies'', Wiley, 2016, Eds. Rath Vannithamby and Shilpa Telwar

S. Maghsudi and S. Stanczak (2015). Communications in Interference-Limited Networks. chapter in 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 in 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, Cambridge University Press, UK, 2014, 262-303.

I. Bjelakovic and H. Boche and J. Sommerfeld (2013). Capacity Results for Arbitrarily Varying Wiretap Channels. In: Aydinian H., Cicalese F., Deppe C. (eds) Information Theory, Combinatorics, and Search Theory. Lecture Notes in Computer Science, vol 7777. Springer, Berlin, Heidelberg

I. Bjelakovic and H. Boche and G. Janen and J. Notzel (2013). Arbitrarily Varying and Compound Classical-Quantum Channels and a Note on Quantum Zero-Error Capacities. In: Aydinian H., Cicalese F., Deppe C. (eds) Information Theory, Combinatorics, and Search Theory. Lecture Notes in Computer Science, vol. 7777. Springer, Berlin, Heidelberg

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

Cooperation dynamics in the networked geometric Brownian motion
Zitatschlüssel Utkov_Coop2019
Autor V. Stojkoski and Z. Utkovski and L. Basnarkov and L. Kocarev
Jahr 2019
DOI https://doi.org/10.1103/PhysRevE.99.062312
Journal Physical Review E 99, 062312, 28 June 2019
Herausgeber American Physical Society
Zusammenfassung Recent works suggest that pooling and sharing may constitute a fundamental mechanism for the evolution of cooperation in well-mixed fluctuating environments. The rationale is that, by reducing the amplitude of fluctuations, pooling and sharing increases the steady-state growth rate at which individuals self-reproduce. However, in reality interactions are seldom realized in a well-mixed structure, and the underlying topology is in general described by a complex network. Motivated by this observation, we investigate the role of the network structure on the cooperative dynamics in fluctuating environments, by developing a model for networked pooling and sharing of resources undergoing a geometric Brownian motion. The study reveals that, while in general cooperation increases the individual steady state growth rates (i.e., is evolutionary advantageous), the interplay with the network structure may yield large discrepancies in the observed individual resource endowments. We comment possible biological and social implications and discuss relations to econophysics.
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Conference, Symposium, and Workshop Papers

Hernangómez, Rodrigo and Bjelakovic, Igor and Servadei, Lorenzo and Sta'nczak, Sławomir (2022). Unsupervised Domain Adaptation across FMCW Radar Configurations Using Margin Disparity Discrepancy. 2022 30th European Signal Processing Conference (EUSIPCO)

Kei Komuro and Masahiro Yukawa and Renato L. G. Cavalcante (2022). Distributed Sparse Optimization Based on Minimax Concave and Consensus Promoting Penalties: Towards Global Optimality. 2022 30th European Signal Processing Conference (EUSIPCO)

Fink, Jochen and Cavalcante, Renato L. G. and Utkovski, Zoran and Sta'nczak, Sławomir (2022). A Set-Theoretic Approach to MIMO Detection. ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 5328–5332.

Hernangómez, Rodrigo and Palaios, Alexandros and Guruvayoorappan, Gayathri and Kasparick, Martin and Ain, Noor Ul and Sta'nczak, Sławomir (2022). Online QoS Estimation for Vehicular Radio Environments. 2022 30th European Signal Processing Conference (EUSIPCO), 5.

Attar, M. Hossein and Taghizadeh, Omid and Chang, Kaxin and Askar, Ramez and Mehlhose, Matthias and Stanczak, Slawomir (2022). Parallel APSM for Fast and Adaptive Digital SIC in Full-Duplex Transceivers with Nonlinearity. 2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

K. Komuro and M. Yukawa and R. L. G. Cavalcante (2021). Distributed Sparse Optimization: Towards Global Optimality using Weakly Convex Regularizers. Proc. IEICE Signal Processing Symposium

D.F. Külzer, F. Debbichi, S. Stanczak and M. Botsov (2021). On Latency Prediction with Deep Learning and Passive Probing at High Mobility. IEEE International Conference on Communications (ICC) 2021, Montreal, Canada (virtual conference), in June 14-23, 2021

M. Frey, I. Bjelakovic and S. Stanczak (2021). Over-The-Air Computation in Correlated Channels. IEEE 2020 Information Theory Workshop (ITW), April 11-15, 2021

D. Schäufele, M. Kasparick, J. Schwardmann, J. Morgenroth and S. Stanczak (2021). Terminal-Side Data Rate Prediction For High-Mobility Users. IEEE 93rd Vehicular Technology Conference (VTC2021-Spring), Helsinki, Finland, April 2021

D.F. Külzer, M. Kasparick, A. Palaios, R. Sattiraju, O. D. Ramos-Cantor, D. Wieruch, H. Tchouankem, F. Göttsch, P. Geuer, J. Schwardmann, G. Fettweis, H.D. Schotten and S. Stanczak (2021). AI4Mobile: Use Cases and Challenges of AI-based QoS Prediction for High-Mobility Scenarios. IEEE Vehicular Technology Conference (VTC Spring) 2021, April 25-28, in Helsinki, Finland



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