Page Content
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T. Piotrowski and R. L. G. Cavalcante (2021).
Fixed points of monotonic and (weakly) scalable neural networks [3].
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 [4]. arXiv preprint
arXiv:2110.11055
M. Frey, I. Bjelakovic and S. Stanczak (2020).
Towards Secure Over-The-Air Computation [5]. 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
[6]. 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 [7]. 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
[8]. 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 [9].
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 [10].
R.L.G. Cavalcante and S. Stanczak (2018).
Fundamental properties of solutions to utility maximization problems
in wireless networks [11]. 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 [12]. Preprint (available at
https://arxiv.org/abs/1609.05080v1)
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Books
S. Stanczak and M. Wiczanowski and H. Boche
(2009). Fundamentals of Resource Allocation in Wireless Networks [15].
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 [16]. 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 [17]. 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 [18].
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 [19]. 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 [20].
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 [21]. 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 [22].
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 [23].
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
[24]. 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 [25]. 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 [26]. Smart Antennas–State-of-the-Art. Hindawi
Publishing Corporation, 521-543.
Journal
Publications
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7 [32] | 8 [33] | 9 [34] | 10 [35] | 11 [36]
next >> [37]
Hernangómez, Rodrigo and Visentin, Tristan and
Servadei, Lorenzo and Khodabakhshandeh, Hamid and Sta'nczak,
Sławomir (2022). Improving Radar Human Activity Classification
Using Synthetic Data with Image Transformation [38]. Sensors.
Multidisciplinary Digital Publishing Institute, 1519.
K. Komuro and M. Yukawa and
R. L. G. Cavalcante (2022). Distributed Sparse
Optimization with Weakly Convex Regularizer: Consensus Promoting and
Approximate Moreau Enhanced Penalties towards Global Optimality [39].
Transactions on Signal and Information Processing over
Networks
K. Komuro and M. Yukawa and
R. L. G. Cavalcante (2022). Distributed Sparse
Optimization with Weakly Convex Regularizer: Consensus Promoting and
Approximate Moreau Enhanced Penalties towards Global Optimality [40].
Transactions on Signal and Information Processing over
Networks
Nicola Kleppmann and Johannes Dommel and Dennis
Wieruch and Stefan Erben (2021). 5G and NOA: Enabling access to
valuable hidden data [41]. atp!info Magazin
M. Frey, I. Bjelakovic and S. Stanczak (2021).
Over-The-Air Computation in Correlated Channels [42]. IEEE
Transactions on Signal Processing
F. Molinari, N. Agrawal, S. Stanczak and J.
Raisch (2021). Max-Consensus Over Fading Wireless Channels [43].
IEEE Transactions on Control of Network Systems, Jan. 2021
M. A. Gutierrez-Estevez, M. Kasparick and S.
Stanczak (2021). Online Learning of Any-to-Any Path Loss Maps [44].
IEEE Communications Letters
J. Dommel, Z. Utkovski, O. Simeone and S.
Stanczak (2021). Joint Source-Channel Coding for Semantics-Aware
Grant-Free Radio Access in IoT Fog Networks [45]. IEEE Signal
Processing Letters
Taghizadeh, Omid and Stanczak, Slawomir and
Iimori, Hiroki and De Abreu, Giuseppe Thadeu Freitas (2021).
Full-Duplex Amplify-and-Forward MIMO Relaying: Design and Performance
Analysis Under Erroneous CSI and Hardware Impairments [46]. IEEE
Open Journal of the Communications Society. IEEE,
1249–1266.
Miretti, Lorenzo and Cavalcante, Renato L.G. and
Stanczak, Slawomir (2021). Channel Covariance Conversion and Modelling
Using Infinite Dimensional Hilbert Spaces [47]. IEEE Transactions
on Signal Processing. IEEE, 3145–3159.
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Conference,
Symposium, and Workshop Papers
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7 [64] | 8 [65] | 9 [66] | 10 [67] | 11 [68] | 12 [69] | 13 [70] | 14
[71] | 15 [72] | 16 [73] | 17 [74] | 18 [75] | 19 [76] | 20 [77] | 21
[78] | 22 [79] | 23 [80] | 24 [81] | 25 [82] | 26 [83] | 27 [84] | 28
[85] | 29 [86] | 30 [87] | 31 [88]
next >> [89]
Hernangómez, Rodrigo and Bjelakovic, Igor and
Servadei, Lorenzo and Sta'nczak, Sławomir (2022). Unsupervised
Domain Adaptation across FMCW Radar Configurations Using Margin
Disparity Discrepancy [90]. 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
[91]. 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 [92]. 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 [93]. 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 [94]. 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 [95]. 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 [96]. 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 [97]. 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 [98]. 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 [99]. IEEE Vehicular Technology
Conference (VTC Spring) 2021, April 25-28, in Helsinki,
Finland
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