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Open AccessJournal ArticleDOI

Error Floor Approximation for LDPC Codes in the AWGN Channel

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TLDR
This paper addresses the prediction of error floors of low-density parity-check codes transmitted over the additive white Gaussian noise channel with modifications that account for the behavior of a nonsaturating decoder and presents the resulting error floor estimates for the Margulis code.
Abstract
This paper addresses the prediction of error floors of low-density parity-check codes transmitted over the additive white Gaussian noise channel. Using a linear state-space model to estimate the behavior of the sum-product algorithm (SPA) decoder in the vicinity of trapping sets (TSs), we study the performance of the SPA decoder in the log-likelihood ratio (LLR) domain as a function of the LLR saturation level. When applied to several widely studied codes, the model accurately predicts a significant decrease in the error floor as the saturation level is allowed to increase. For nonsaturating decoders, however, we find that the state-space model breaks down after a small number of iterations due to the strong correlation of LLR messages. We then revisit Richardson's importance-sampling methodology for estimating error floors due to TSs when those floors are too low for Monte Carlo simulation. We propose modifications that account for the behavior of a nonsaturating decoder and present the resulting error floor estimates for the Margulis code. These estimates are much lower, significantly steeper, and more sensitive to iteration count than those previously reported.

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Citations
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Journal ArticleDOI

Finite Alphabet Iterative Decoders—Part I: Decoding Beyond Belief Propagation on the Binary Symmetric Channel

TL;DR: It is shown that there exist FAIDs that surpass the floating-point BP decoder in the error floor region while requiring only three bits of precision for the representation of the messages, and FAIDs are able to achieve a superior performance at much lower complexity.
Journal ArticleDOI

The ADMM Penalized Decoder for LDPC Codes

TL;DR: A new class of decoders obtained by applying the alternating direction method of multipliers (ADMM) algorithm to a set of non-convex optimization problems are constructed by adding a penalty term to the objective of LP decoding to make pseudocodewords, which are non-integer vertices of the LP relaxation, more costly.
Journal ArticleDOI

New Characterization and Efficient Exhaustive Search Algorithm for Leafless Elementary Trapping Sets of Variable-Regular LDPC Codes

TL;DR: It is proved that using the three expansion techniques, any LETS structure can be obtained starting from a simple cycle, no matter how large the size of the structure a or the number of its unsatisfied check nodes b are, and that for the proposed characterization/ search to exhaustively cover all the LETS structures within the (a, b) classes, the length of the short cycles required to be enumerated is less than that of the LSS-based characterization/search.
Posted Content

Quantized Iterative Message Passing Decoders with Low Error Floor for LDPC Codes

TL;DR: In this article, the authors proposed a (q+1)-bit quasi-uniform quantization method to increase the dynamic range of messages, thereby overcoming a limitation of conventional quantization schemes.
Proceedings ArticleDOI

Quantized min-sum decoders with low error floor for LDPC codes

TL;DR: It is shown that one source of the error floors observed in the literature may be the message quantization rule used in the iterative decoder implementation, and a new quantization method is proposed to overcome the limitations of standard quantization rules.
References
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Journal ArticleDOI

Factor graphs and the sum-product algorithm

TL;DR: A generic message-passing algorithm, the sum-product algorithm, that operates in a factor graph, that computes-either exactly or approximately-various marginal functions derived from the global function.
Book

Matrix Analysis and Applied Linear Algebra

TL;DR: The author presents Perron-Frobenius theory of nonnegative matrices Index, a theory of matrices that combines linear equations, vector spaces, and matrix algebra with insights into eigenvalues and Eigenvectors.
Journal ArticleDOI

On the design of low-density parity-check codes within 0.0045 dB of the Shannon limit

TL;DR: Improved algorithms are developed to construct good low-density parity-check codes that approach the Shannon limit very closely, especially for rate 1/2.
Journal ArticleDOI

Analysis of sum-product decoding of low-density parity-check codes using a Gaussian approximation

TL;DR: By using the Gaussian approximation for message densities under density evolution, the sum-product decoding algorithm can be visualize and the optimization of degree distributions can be understood and done graphically using the visualization.
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