S. Stanczak and M. Wiczanowski and H. Boche (2009). Fundamentals of Resource Allocation in Wireless Networks [8]. 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 [9]. Lecture Notes in Computer Science (LNCS 4000). Springer, Berlin, 2006. Springer, Berlin.

S. Stanczak and A. Keller and R.L.G. Cavalcante and N. Binder (2021). Long-term Perspectives: Machine Learning for Future Wireless Networks [10]. 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 [11]. Machine Learning for Future Wireless Communications. Wiley & IEEE Press, 15.

S. Maghsudi and S. Stanczak (2015). Communications in Interference-Limited Networks [12]. 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 [13]. 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 [14]. chapter Cognitive Radio and Sharing Unlicensed Spectrum in the book Mechanisms and Games for Dynamic Spectrum Allocation, 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 [15]. Smart Antennas–State-of-the-Art. Hindawi Publishing Corporation, 521-543.

M. Frey, I. Bjelakovic and S. Stanczak (2021). Over-The-Air Computation in Correlated Channels [23]. IEEE Transactions on Signal Processing

F. Molinari, N. Agrawal, S. Stanczak and J. Raisch (2021). Max-Consensus Over Fading Wireless Channels [24]. 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 [25]. 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 [26]. IEEE Signal Processing Letters

Fink, Jochen and Cavalcante, Renato Luís Garrido and Stanczak, Slawomir (2021). Multi-Group Multicast Beamforming by Superiorized Projections Onto Convex Sets [27]. IEEE Transactions on Signal Processing, 5708-5722.

Fink, Jochen and Cavalcante, Renato Luís Garrido and Stanczak, Slawomir (2021). Multi-Group Multicast Beamforming by Superiorized Projections Onto Convex Sets [28]. IEEE Transactions on Signal Processing, 5708-5722.

Miretti, Lorenzo and Cavalcante, Renato Luis Garrido and Stanczak, Slawomir (2021). Channel Covariance Conversion and Modelling Using Infinite Dimensional Hilbert Spaces [29]. IEEE Transactions on Signal Processing. IEEE, 3145–3159.

Vural, Metin and Aravkin, Aleksandr Y. and Stanczak, Slawomir (2021). l1-Norm Minimization With Regula Falsi Type Root Finding Methods [30]. IEEE Signal Processing Letters, 2132-2136.

D. A. Awan and R. L.G. Cavalcante and S. Stanczak (2020). Robust Cell-Load Learning with a Small Sample Set [31]. IEEE Transactions on Signal Processing (TSP), 68:270-283.

C.-X. Wang and M. Di Renzo and S. Stanczak and S. Wang and E. G. Larsson (2020). Artificial Intelligence Enabled Wireless Networking for 5G and Beyond: Recent Advances and Future Challenges [32]. IEEE Wireless Communications Magazine, February 2020/Intelligent Radio: When Artificial Intelligence Meets Radio Network