Search Results for author: Gerhard Wunder

Found 7 papers, 1 papers with code

A Reverse Jensen Inequality Result with Application to Mutual Information Estimation

no code implementations12 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.

Mutual Information Estimation

Explicit CSI Feedback Compression via Learned Approximate Message Passing

no code implementations12 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.

Reinforce Security: A Model-Free Approach Towards Secure Wiretap Coding

no code implementations1 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.

Mutual Information Estimation reinforcement-learning

ComPass: Proximity Aware Common Passphrase Agreement Protocol for Wi-Fi devices Using Physical Layer Security

no code implementations11 Mar 2021 Khan Reaz, Gerhard Wunder

Secure and scalable device provisioning is a notorious challenge in Wi-Fi.

Cryptography and Security

Using AoI Forecasts in Communicating and Robust Distributed Model-Predictive Control

no code implementations9 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

Deep Learning for Channel Coding via Neural Mutual Information Estimation

1 code implementation7 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.

Mutual Information Estimation

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