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相关论文: The Velocity of the Propagating Wave for Spatially…

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We consider the dynamics of belief propagation decoding of spatially coupled Low-Density Parity-Check codes. It has been conjectured that after a short transient phase, the profile of "error probabilities" along the spatial direction of a…

信息论 · 计算机科学 2017-01-16 Rafah El-Khatib , Nicolas Macris

We consider spatially coupled systems governed by a set of scalar density evolution equations. Such equations track the behavior of message-passing algorithms used, for example, in coding, sparse sensing, or constraint-satisfaction…

信息论 · 计算机科学 2017-01-16 Rafah El-Khatib , Nicolas Macris

Spatially coupled low-density parity-check codes show an outstanding performance under the low-complexity belief propagation (BP) decoding algorithm. They exhibit a peculiar convergence phenomenon above the BP threshold of the underlying…

信息论 · 计算机科学 2013-07-16 Vahid Aref , Laurent Schmalen , Stephan ten Brink

It is known that windowed decoding (WD) can effectively balance the performance and complexity of spatially coupled low-density parity-check (LDPC) codes. In this study, we show that information can propagate in a wave-like manner at a…

信息论 · 计算机科学 2025-07-10 Qingqing Peng , Dongxu Chang , Guanghui Wang , Guiying Yan

We consider spatially coupled low-density parity-check codes with finite smoothing parameters. A finite smoothing parameter is important for designing practical codes that are decoded using low-complexity windowed decoders. By optimizing…

信息论 · 计算机科学 2019-07-09 Laurent Schmalen , Vahid Aref

We present a decode-and-forward transmission scheme based on spatially-coupled low-density parity-check (SC-LDPC) codes for a network consisting of two (possibly correlated) sources, one relay, and one destination. The links between the…

信息论 · 计算机科学 2014-02-17 Stefan Schwandter , Alexandre Graell i Amat , Gerald Matz

Spatially-coupled LDPC codes are known to have excellent asymptotic properties. Much less is known regarding their finite-length performance. We propose a scaling law to predict the error probability of finite-length spatially-coupled…

信息论 · 计算机科学 2015-05-26 Pablo M. Olmos , Rüdiger Urbanke

The peeling decoding for spatially coupled low-density parity-check (SC-LDPC) codes is analyzed for a binary erasure channel. An analytical calculation of the mean evolution of degree-one check nodes of protograph-based SC-LDPC codes is…

信息论 · 计算机科学 2014-02-03 Markus Stinner Pablo M. Olmos

Low-Density Parity-Check (LDPC) codes received much attention recently due to their capacity-approaching performance. The iterative message-passing algorithm is a widely adopted decoding algorithm for LDPC codes \cite{Kschischang01}. An…

信息论 · 计算机科学 2009-08-27 Xudong Ma , En-hui Yang

The equivalence of peeling decoding (PD) and Belief Propagation (BP) for low-density parity-check (LDPC) codes over the binary erasure channel is analyzed. Modifying the scheduling for PD, it is shown that exactly the same variable nodes…

信息论 · 计算机科学 2016-04-19 Markus Stinner , Luca Barletta , Pablo M. Olmos

Low-density parity-check (LDPC) convolutional codes have been shown to exhibit excellent performance under low-complexity belief-propagation decoding [1], [2]. This phenomenon is now termed threshold saturation via spatial coupling. The…

信息论 · 计算机科学 2013-12-30 Santhosh Kumar , Andrew J. Young , Nicolas Macris , Henry D. Pfister

This paper considers density evolution for lowdensity parity-check (LDPC) and multi-edge type low-density parity-check (MET-LDPC) codes over the binary input additive white Gaussian noise channel. We first analyze three singleparameter…

In this paper, we study the density evolution analysis of spatially coupled low-density parity-check (SC-LDPC) codes over binary input additive white Gaussian noise (BIAWGN) channels under the belief propagation (BP) decoding algorithm.…

信息论 · 计算机科学 2015-10-19 Md. Noor-A-Rahim , Gottfried Lechner , Khoa D. Nguyen

Density evolution (DE) is one of the most powerful analytical tools for low-density parity-check (LDPC) codes on memoryless binary-input/symmetric-output channels. The case of non-symmetric channels is tackled either by the LDPC coset code…

信息论 · 计算机科学 2007-07-13 Chih-Chun Wang , H. Vincent Poor , Sanjeev R. Kulkarni

We consider spatially coupled low-density parity-check codes with finite smoothing parameters. A finite smoothing parameter is important for designing practical codes that are decoded using low-complexity windowed decoders. By optimizing…

信息论 · 计算机科学 2017-01-27 Laurent Schmalen , Vahid Aref , Fanny Jardel

Low-density parity-check (LDPC) convolutional codes (or spatially-coupled codes) have been shown to approach capacity on the binary erasure channel (BEC) and binary-input memoryless symmetric channels. The mechanism behind this spectacular…

信息论 · 计算机科学 2015-03-20 Arvind Yedla , Yung-Yih Jian , Phong S. Nguyen , Henry D. Pfister

Density evolution is one of the most powerful analytical tools for low-density parity-check (LDPC) codes and graph codes with message passing decoding algorithms. With channel symmetry as one of its fundamental assumptions, density…

信息论 · 计算机科学 2007-07-16 C. -C. Wang , S. R. Kulkarni , H. V. Poor

Spatially-coupled low-density parity-check (LDPC) codes, which were first introduced as LDPC convolutional codes, have been shown to exhibit excellent performance under low-complexity belief-propagation decoding. This phenomenon is now…

信息论 · 计算机科学 2015-01-16 Santhosh Kumar , Andrew J. Young , Nicolas Macris , Henry D. Pfister

A class of doubly-generalized low-density parity-check (D-GLDPC) codes, where single parity-check (SPC) codes are used as variable nodes (VNs), is investigated. An expression for the growth rate of the weight distribution of any D-GLDPC…

信息论 · 计算机科学 2016-11-17 E. Paolini , M. F. Flanagan , M. Chiani , M. P. C. Fossorier

Generalized low-density parity-check (GLDPC) codes are a class of LDPC codes in which the standard single parity check (SPC) constraints are replaced by constraints defined by a linear block code. These stronger constraints typically result…

信息论 · 计算机科学 2021-04-19 David G. M. Mitchell , Pablo M. Olmos , Michael Lentmaier , Daniel J. Costello
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