Journal ArticleDOI
Reduced complexity iterative decoding of low-density parity check codes based on belief propagation
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Two simplified versions of the belief propagation algorithm for fast iterative decoding of low-density parity check codes on the additive white Gaussian noise channel are proposed, which greatly simplifies the decoding complexity of belief propagation.Abstract:
Two simplified versions of the belief propagation algorithm for fast iterative decoding of low-density parity check codes on the additive white Gaussian noise channel are proposed. Both versions are implemented with real additions only, which greatly simplifies the decoding complexity of belief propagation in which products of probabilities have to be computed. Also, these two algorithms do not require any knowledge about the channel characteristics. Both algorithms yield a good performance-complexity trade-off and can be efficiently implemented in software as well as in hardware, with possibly quantized received values.read more
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Proceedings ArticleDOI
Investigations on performance analysis of various soft decision based LDPC decoding algorithms
TL;DR: This paper focuses on research issues related to decoding of various Low-Density Parity-Check (LDPC) codes, which exhibit excellent decoding performance with reduced computational complexity.
Proceedings ArticleDOI
A low-hardware consumption FPGA based configurable LDPC decoder
Lijun Zhang,Ying Jiang +1 more
TL;DR: This paper proposes a low-consumption configurable decoder architecture and a universal mapping algorithm for extrinsic messages to cope with structured or random regular LDPC codes and can be implemented in low-priced products such as XILINX Spartan FPGAs family.
Journal Article
Research on Decoding Algorithm of LDPC Code
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Implementatieaspecten van een LDPC decoder in een FPGA
TL;DR: This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology.
References
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Book
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
TL;DR: Probabilistic Reasoning in Intelligent Systems as mentioned in this paper is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty, and provides a coherent explication of probability as a language for reasoning with partial belief.
Book
Low-Density Parity-Check Codes
TL;DR: A simple but nonoptimum decoding scheme operating directly from the channel a posteriori probabilities is described and the probability of error using this decoder on a binary symmetric channel is shown to decrease at least exponentially with a root of the block length.
Journal ArticleDOI
Good error-correcting codes based on very sparse matrices
TL;DR: It is proved that sequences of codes exist which, when optimally decoded, achieve information rates up to the Shannon limit, and experimental results for binary-symmetric channels and Gaussian channels demonstrate that practical performance substantially better than that of standard convolutional and concatenated codes can be achieved.
Journal ArticleDOI
A recursive approach to low complexity codes
TL;DR: It is shown that choosing a transmission order for the digits that is appropriate for the graph and the subcodes can give the code excellent burst-error correction abilities.
Journal ArticleDOI
Near Shannon limit performance of low density parity check codes
TL;DR: The authors report the empirical performance of Gallager's low density parity check codes on Gaussian channels, showing that performance substantially better than that of standard convolutional and concatenated codes can be achieved.