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Reduced complexity iterative decoding of low-density parity check codes based on belief propagation

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TLDR
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.

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Citations
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Patent

Procédé de codage, procédé de décodage, codeur et décodeur

村上豊
TL;DR: In this paper, the authors present a procedure de codage LDPC-CC (Low-Density Parity-Check Convolutional Codes) for cycle variants of codes.
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Bounds on Pairwise Error Probability for LDPC coded CF-mMIMO System

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Conflict-Free Vectorized In-order In-place Radix-r Belief Propagation Polar Code Decoder Algorithm

TL;DR: A vectorized in-order in-place belief propagation polar code decoder algorithm where all stages access vectorized data from memory that results in a high throughput because vectors of elements can be fetched from and stored in memory in each clock cycle.
Proceedings ArticleDOI

Memory-Centric Flooded LDPC Decoder Architecture Using Non-surjective Finite Alphabet Iterative Decoding

TL;DR: Non-Surjective Finite Alphabet Iterative Decoding represents an LDPC decoding algorithm that uses reduced message storage, with similar or improved error correction performance with respect to Min-Sum, and estimates indicate that employing NS-FAID compression tables yield improvements between 25% and 110% in Throughput to Area Ratio (TAR).
Proceedings ArticleDOI

Performance Analysis of LDPC Coding under Multiple Scattering in Ultraviolet Communication

TL;DR: In this paper , a simulated Ultraviolet (UV) communication system based on binary phase shift keying (BPSK) modulation is built, and the effects of different decoding algorithms, number of iterations, and different receiver field-of-view (FOV) angles on the performance of the UV communication system are analyzed, respectively.
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.
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