no code implementations • 12 Nov 2021 • Gerhard Wunder, Benedikt Groß, Rick Fritschek, Rafael F. Schaefer
The Jensen inequality is a widely used tool in a multitude of fields, such as for example information theory and machine learning.
no code implementations • 12 Oct 2021 • Benedikt Groß, Rana Ahmed Salem, Thorsten Wild, Gerhard Wunder
Explicit channel state information at the transmitter side is helpful to improve downlink precoding performance for multi-user MIMO systems.
no code implementations • 1 Jun 2021 • Rick Fritschek, Rafael F. Schaefer, Gerhard Wunder
The use of deep learning-based techniques for approximating secure encoding functions has attracted considerable interest in wireless communications due to impressive results obtained for general coding and decoding tasks for wireless communication systems.
no code implementations • 11 Mar 2021 • Khan Reaz, Gerhard Wunder
Secure and scalable device provisioning is a notorious challenge in Wi-Fi.
Cryptography and Security
no code implementations • 9 Mar 2021 • Jannik Hahn, Richard Schoeffauer, Gerhard Wunder, Olaf Stursberg
By contrast, the present approachestablishes a robust distributed model-predictive controlscheme, in which the local subsystem controllers oper-ate under the assumption of a variable communicationschedule that is predicted by a network controller.
Systems and Control Systems and Control
1 code implementation • 7 Mar 2019 • Rick Fritschek, Rafael F. Schaefer, Gerhard Wunder
However, one of the drawbacks of current learning approaches is that a differentiable channel model is needed for the training of the underlying neural networks.
no code implementations • 9 May 2017 • Mahdi Barzegar Khalilsarai, Saeid Haghighatshoar, Giuseppe Caire, Gerhard Wunder
To design such a blind predictor, we use the random spectral representation of a stationary Gaussian process.