887 citations · 1.2k across the 50 of their papers we have counts for
41 papers · 1 filter
When to Stop? Dynamic Early Termination of Sequential Ensembles
Paul Bezner, Felix Krieg, Stephan ten Brink
Ordered-statistics decoding (OSD) post-processing substantially improves the performance of belief propagation (BP) ensembles, but it also removes their natural syndrome-based stop…
SECS: A Soft Ensemble-Combining Stage for Low-Latency Decoding
Felix Krieg, Paul Bezner, Stephan ten Brink
Ensemble decoding is a promising technique for ultra-reliable low-latency communication, as it trades hardware parallelism for decoding latency by running M diverse belief propagat…
Row-Boosted Ensemble Belief Propagation for Short LDPC Codes
Paul Bezner, Felix Krieg, Stephan ten Brink
Belief-propagation (BP) decoding of short and moderate-length low-density parity-check (LDPC) codes is limited by finite-length graph effects: a single decoder trajectory can becom…
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…
Chase-like Decoding: Test-Pattern Design and Performance Analysis
Tim Janz, Simon Obermüller, Andreas Zunker +1
Chase-like decoding algorithms are a popular choice for soft-input decoding of algebraic codes. We evaluate different test-pattern sets for Chase-like decoding. Structured sets, su…
Signal Space-Transformed Expectation Propagation for Symbol Detection in ISI Channels
Jannis Clausius, Luca Schmid, Laurent Schmalen +1
Iterative message passing detection based on expectation propagation (EP) has demonstrated near-optimum performance in many signal processing and communication scenarios. The metho…
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…
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…
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…
Row-Merged Polar Codes: Analysis, Design and Decoder Implementation
Andreas Zunker, Marvin Geiselhart, Lucas Johannsen +4
Row-merged polar codes are a family of pre-transformed polar codes (PTPCs) with little precoding overhead. Providing an improved distance spectrum over plain polar codes, they are…
Augmenting Channel Charting with Classical Wireless Source Localization Techniques
Florian Euchner, Phillip Stephan, Stephan ten Brink
Channel Charting aims to construct a map of the radio environment by leveraging similarity relationships found in high-dimensional channel state information. Although resulting cha…
Learning Radio Environments by Differentiable Ray Tracing
Jakob Hoydis, Fayçal Aït Aoudia, Sebastian Cammerer +4
Ray tracing (RT) is instrumental in 6G research in order to generate spatially-consistent and environment-specific channel impulse responses (CIRs). While acquiring accurate scene…
Enumeration of Minimum Weight Codewords of Pre-Transformed Polar Codes by Tree Intersection
Andreas Zunker, Marvin Geiselhart, Stephan ten Brink
Pre-transformed polar codes (PTPCs) form a class of codes that perform close to the finite-length capacity bounds. The minimum distance and the number of minimum weight codewords a…
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…
Successive Cancellation Automorphism List Decoding of Polar Codes
Lucas Johannsen, Claus Kestel, Marvin Geiselhart +3
The discovery of suitable automorphisms of polar codes gained a lot of attention by applying them in Automorphism Ensemble Decoding (AED) to improve the error-correction performanc…
Component Training of Turbo Autoencoders
Jannis Clausius, Marvin Geiselhart, Stephan ten Brink
Isolated training with Gaussian priors (TGP) of the component autoencoders of turbo-autoencoder architectures enables faster, more consistent training and better generalization to…
Phase-Equivariant Polar Coded Modulation
Marvin Geiselhart, Marc Gauger, Felix Krieg +2
For short-packet, low-latency communications over random access channels, piloting overhead significantly reduces spectral efficiency. Therefore, pilotless systems recently gained…
Rate-Compatible Polar Codes for Automorphism Ensemble Decoding
Marvin Geiselhart, Jannis Clausius, Stephan ten Brink
Recently, automorphism ensemble decoding (AED) has drawn research interest as a more computationally efficient alternative to successive cancellation list (SCL) decoding of polar c…
Automorphism Ensemble Polar Code Decoders for 6G URLLC
Claus Kestel, Marvin Geiselhart, Lucas Johannsen +2
The URLLC scenario in the upcoming 6G standard requires low latency and ultra reliable transmission, i.e., error correction towards ML performance. Achieving near-ML performance is…
Deep Reinforcement Learning for mmWave Initial Beam Alignment
Daniel Tandler, Sebastian Dörner, Marc Gauger +1
We investigate the applicability of deep reinforcement learning algorithms to the adaptive initial access beam alignment problem for mmWave communications using the state-of-the-ar…
Optimizing Serially Concatenated Neural Codes with Classical Decoders
Jannis Clausius, Marvin Geiselhart, Stephan ten Brink
For improving short-length codes, we demonstrate that classic decoders can also be used with real-valued, neural encoders, i.e., deep-learning based codeword sequence generators. H…
Learning Quantization in LDPC Decoders
Marvin Geiselhart, Ahmed Elkelesh, Jannis Clausius +4
Finding optimal message quantization is a key requirement for low complexity belief propagation (BP) decoding. To this end, we propose a floating-point surrogate model that imitate…
Introducing -lifting for Learning Nonlinear Pulse Shaping in Coherent Optical Communication
Tim Uhlemann, Alexander Span, Sebastian Dörner +1
Pulse shaping for coherent optical fiber communication has been an active area of research for the past decade. Most of the early schemes are based on classic Nyquist pulse shaping…