activity
20162024
most citedOn Deep Learning-Based Channel Decoding

47 citations · 84 across the 24 of their papers we have counts for

collaborators

24 papers

cs.IT2024

ESPARGOS: Phase-Coherent WiFi CSI Datasets for Wireless Sensing Research

Florian Euchner, Stephan ten Brink

The use of WiFi signals to sense the physical environment is gaining popularity, with some common applications being motion detection and transmitter localization. Standard-complia…

cs.IT2024

Leveraging the Doppler Effect for Channel Charting

Florian Euchner, Phillip Stephan, Stephan ten Brink

Channel Charting is a dimensionality reduction technique that reconstructs a map of the radio environment from similarity relationships found in channel state information. Distance…

cs.IT2024

GAN-based Massive MIMO Channel Model Trained on Measured Data

Florian Euchner, Janina Sanzi, Marcus Henninger +1

Wireless channel models are a commonly used tool for the development of wireless telecommunication systems and standards. The currently prevailing geometry-based stochastic channel…

cs.IT20241 cited

Graph Neural Network-based Joint Equalization and Decoding

Jannis Clausius, Marvin Geiselhart, Daniel Tandler +1

This paper proposes to use graph neural networks (GNNs) for equalization, that can also be used to perform joint equalization and decoding (JED). For equalization, the GNN is build…

cs.IT2024

Deep Learning Based Adaptive Joint mmWave Beam Alignment

Daniel Tandler, Marc Gauger, Ahmet Serdar Tan +2

The challenging propagation environment, combined with the hardware limitations of mmWave systems, gives rise to the need for accurate initial access beam alignment strategies with…

cs.IT2023

Angle-Delay Profile-Based and Timestamp-Aided Dissimilarity Metrics for Channel Charting

Phillip Stephan, Florian Euchner, Stephan ten Brink

Channel charting is a self-supervised learning technique whose objective is to reconstruct a map of the radio environment, called channel chart, by taking advantage of similarity r…