239 citations · 695 across the 67 of their papers we have counts for
9 papers · 1 filter
A Reverse Jensen Inequality Result with Application to Mutual Information Estimation
Gerhard Wunder, Benedikt Groß, Rick Fritschek +1
The Jensen inequality is a widely used tool in a multitude of fields, such as for example information theory and machine learning. It can be also used to derive other standard ineq…
Guaranteed blind deconvolution and demixing via hierarchically sparse reconstruction
Axel Flinth, Ingo Roth, Benedikt Groß +2
The blind deconvolution problem amounts to reconstructing both a signal and a filter from the convolution of these two. It constitutes a prominent topic in mathematical and enginee…
Explicit CSI Feedback Compression via Learned Approximate Message Passing
Benedikt Groß, Rana Ahmed Salem, Thorsten Wild +1
Explicit channel state information at the transmitter side is helpful to improve downlink precoding performance for multi-user MIMO systems. In order to reduce feedback signalling…
Reinforce Security: A Model-Free Approach Towards Secure Wiretap Coding
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 obtai…
Measure Concentration on the OFDM-based Random Access Channel
Gerhard Wunder, Axel Flinth, Benedikt Groß
It is well known that CS can boost massive random access protocols. Usually, the protocols operate in some overloaded regime where the sparsity can be exploited. In this paper, we…
Hierarchical sparse recovery from hierarchically structured measurements with application to massive random access
Benedikt Groß, Axel Flinth, Ingo Roth +2
A new family of operators, coined hierarchical measurement operators, is introduced and discussed within the well-known hierarchical sparse recovery framework. Such operator is a c…