16 citations · 36 across the 16 of their papers we have counts for
20 papers
A Comparative Study of Ensemble Decoding Methods for Short Length LDPC Codes
Felix Krieg, Jannis Clausius, Marvin Geiselhart +1
To alleviate the suboptimal performance of belief propagation (BP) decoding of short low-density parity-check (LDPC) codes, a plethora of improved decoding algorithms has been prop…
Bounds for Joint Detection and Decoding on the Binary-Input AWGN Channel
Simon Obermüller, Jannis Clausius, Marvin Geiselhart +1
For asynchronous transmission of short blocks, preambles for packet detection contribute a non-negligible overhead. To reduce the required preamble length, joint detection and deco…
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…
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…
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…
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…
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…
Graph Search based Polar Code Design
Marvin Geiselhart, Andreas Zunker, Ahmed Elkelesh +2
It is well known that to fulfill their full potential, the design of polar codes must be tailored to their intended decoding algorithm. While for successive cancellation (SC) decod…
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…
A Polar Subcode Approach to Belief Propagation List Decoding
Marvin Geiselhart, Ahmed Elkelesh, Jannis Clausius +1
Permutation decoding gained recent interest as it can exploit the symmetries of a code in a parallel fashion. Moreover, it has been shown that by viewing permuted polar codes as po…
Automorphism Ensemble Decoding of Quasi-Cyclic LDPC Codes by Breaking Graph Symmetries
Marvin Geiselhart, Moustafa Ebada, Ahmed Elkelesh +2
We consider automorphism ensemble decoding (AED) of quasi-cyclic (QC) low-density parity-check (LDPC) codes. Belief propagation (BP) decoding on the conventional factor graph is eq…
Iterative Reed-Muller Decoding
Marvin Geiselhart, Ahmed Elkelesh, Moustafa Ebada +2
Reed-Muller (RM) codes are known for their good maximum likelihood (ML) performance in the short block-length regime. Despite being one of the oldest classes of channel codes, find…
On the Automorphism Group of Polar Codes
Marvin Geiselhart, Ahmed Elkelesh, Moustafa Ebada +2
The automorphism group of a code is the set of permutations of the codeword symbols that map the whole code onto itself. For polar codes, only a part of the automorphism group was…
Iterative Detection and Decoding of Finite-Length Polar Codes in Gaussian Multiple Access Channels
Moustafa Ebada, Sebastian Cammerer, Ahmed Elkelesh +2
We consider the usage of finite-length polar codes for the Gaussian multiple access channel (GMAC) with a finite number of users. Based on the interleave-division multipleaccess (I…
Automorphism Ensemble Decoding of Reed-Muller Codes
Marvin Geiselhart, Ahmed Elkelesh, Moustafa Ebada +2
Reed-Muller (RM) codes are known for their good maximum likelihood (ML) performance in the short block-length regime. Despite being one of the oldest classes of channel codes, find…
CRC-Aided Belief Propagation List Decoding of Polar Codes
Marvin Geiselhart, Ahmed Elkelesh, Moustafa Ebada +2
Although iterative decoding of polar codes has recently made huge progress based on the idea of permuted factor graphs, it still suffers from a non-negligible performance degradati…