6 papers · 1 filter
Auxiliary Nodes for BP Decoding of Quantum LDPC Codes
Daniel Tandler, Paul Bezner, Stephan ten Brink
Many recently proposed Calderbank-Shor-Steane (CSS) quantum low-density parity-check (QLDPC) codes have sparse decoding graphs, enabling syndrome-based belief propagation (BP) deco…
Towards a Unified Coding Scheme for 6G
Paul Bezner, Erdem Eray Cil, Jannis Clausius +14
The growing demand for higher data rates necessitates continuous innovations in wireless communication systems, particularly with the emergence of 6G. Channel coding plays a crucia…
Joint Detection and Decoding: A Graph Neural Network Approach
Jannis Clausius, Marvin Rübenacke, Daniel Tandler +1
Narrowing the performance gap between optimal and feasible detection in inter-symbol interference (ISI) channels, this paper proposes to use graph neural networks (GNNs) for detect…
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…
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…
On Recurrent Neural Networks for Sequence-based Processing in Communications
Daniel Tandler, Sebastian Dörner, Sebastian Cammerer +1
In this work, we analyze the capabilities and practical limitations of neural networks (NNs) for sequence-based signal processing which can be seen as an omnipresent property in al…