The ‘threshold’ of a code ensemble can be defined as the noise level at which the block error probability curve crosses 1/2. For ensembles of low-density parity check codes used over the binary erasure channel, the behavior of the threshold for large blocklengths is known in detail. It is characterized by an asymptotic threshold value, and a finite-blocklength shift parameter. Here we present a new method for computing the shift parameter that can be applied to general binary memoryless symmetric channels, and general message passing algorithms. We check that the new approach recovers the known parameters for erasure correction.The ‘threshold’ of a code ensemble can be defined as the noise level at which the block error probability curve crosses 1/2. For ensembles of low-density parity check codes used over the binary erasure channel, the behavior of the threshold for large blocklengths is known in detail. It is characterized by an asymptotic threshold value, and a finite-blocklength shift parameter. Here we present a new method for computing the shift parameter that can be applied to general binary memoryless symmetric channels, and general message passing algorithms. We check that the new approach recovers the known parameters for erasure correction.

NoneJan 1, 20080 citations

Finite-Length Scaling and Finite-Length Shift for Low-Density Parity-Check Codes

Amraoui, Abdelaziz, Andrea Montanari A, Richardson, Tom +1 more

Consider communication over the binary erasure channel BEC using random low-density parity-check codes with finite-blocklength n from `standard' ensembles. We show that large error events is conveniently described within a scaling theory, and explain how to estimate heuristically their effect. Among other quantities, we consider the finite length threshold e(n), defined by requiring a block error probability P_B = 1/2. For ensembles with minimum variable degree larger than two, the following expression is argued to hold e(n) = e -e_1 n^{-2/3} +Θ(n^{-1}) with a calculable shift} parameter e_1>0.Consider communication over the binary erasure channel BEC using random low-density parity-check codes with finite-blocklength n from `standard' ensembles. We show that large error events is conveniently described within a scaling theory, and explain how to estimate heuristically their effect. Among other quantities, we consider the finite length threshold e(n), defined by requiring a block error probability P_B = 1/2. For ensembles with minimum variable degree larger than two, the following expression is argued to hold e(n) = e -e_1 n^{-2/3} +Θ(n^{-1}) with a calculable shift} parameter e_1>0.

arXiv:cs/0410019Oct 10, 20046 citations

The slope scaling parameter for general channels, decoders, and ensembles

Jeremie Ezri, Andrea Montanari A, Sewoong Oh +1 more

Scaling laws are a powerful way to analyze the performance of moderately sized iteratively decoded sparse graph codes. Our aim is to provide an easily usable finite-length optimization tool that is applicable to the wide variety of channels, blocklengths, error probability requirements, and decoders that one encounters for practical systems. The tool is aimed at non-experts in the field, who need to quickly find code designs that are comparable with the best known codes available today but do not have the luxury of spending months in doing so. In previous work we have shown how to compute scaling parameters for transmission over the binary erasure channel, as well as general channels and general quantized message-passing decoders when applied to regular ensembles. In this paper we show how to compute the message variance for a fixed number of iterations for irregular low-density parity-check ensembles. From these calculations the basic scaling parameter alpha can be deduced by determining the leading term of the limiting expression when the number of iterations tends to infinity and the channel parameter approaches the density evolution threshold.Scaling laws are a powerful way to analyze the performance of moderately sized iteratively decoded sparse graph codes. Our aim is to provide an easily usable finite-length optimization tool that is applicable to the wide variety of channels, blocklengths, error probability requirements, and decoders that one encounters for practical systems. The tool is aimed at non-experts in the field, who need to quickly find code designs that are comparable with the best known codes available today but do not have the luxury of spending months in doing so. In previous work we have shown how to compute scaling parameters for transmission over the binary erasure channel, as well as general channels and general quantized message-passing decoders when applied to regular ensembles. In this paper we show how to compute the message variance for a fixed number of iterations for irregular low-density parity-check ensembles. From these calculations the basic scaling parameter alpha can be deduced by determining the leading term of the limiting expression when the number of iterations tends to infinity and the channel parameter approaches the density evolution threshold.

IEEE International Symposium on Information Theory (ISIT)Jul 1, 200817 citations

Density evolution, thresholds and the stability condition for non-binary LDPC codes

Vishwambhar Rathi, Rudiger L. Urbanke

The density evolution equations for non-binary low-density parity-check (LDPC) ensembles when transmission takes place over the binary erasure channel are derived. Ensembles defined with respect to the general linear group over the binary field are introduced. For these ensembles the density evolution equations can be written compactly. The density evolution for the general linear group helps in understanding the density evolution for codes defined with respect to finite fields. Thresholds are computed for different alphabet sizes for various LDPC ensembles. Surprisingly, the threshold is not a monotonic function of the alphabet size. The stability condition for non-binary LDPC ensembles over any binary memoryless symmetric channel is stated. Upper bounds on the MAP thresholds for various non-binary ensembles based on EXIT curves and the area theorem are given.The density evolution equations for non-binary low-density parity-check (LDPC) ensembles when transmission takes place over the binary erasure channel are derived. Ensembles defined with respect to the general linear group over the binary field are introduced. For these ensembles the density evolution equations can be written compactly. The density evolution for the general linear group helps in understanding the density evolution for codes defined with respect to finite fields. Thresholds are computed for different alphabet sizes for various LDPC ensembles. Surprisingly, the threshold is not a monotonic function of the alphabet size. The stability condition for non-binary LDPC ensembles over any binary memoryless symmetric channel is stated. Upper bounds on the MAP thresholds for various non-binary ensembles based on EXIT curves and the area theorem are given.

arXiv:cs/0511100IEE Proceedings - CommunicationsJan 1, 2005101 citations

Exact thresholds for low-density parity-check codes over the binary erasure channel

Jianjun Mu, Xiaopeng Jiao, Xinmei Wang

A simple method for determining the threshold of irregular LDPC codes over the binary erasure channel (BEC) under message-passing decoding is proposed. An exact formula for calculating the threshold of irregular LDPC codes over the BEC is proved. This generalizes the known result on the threshold of regular LDPC codes to irregular LDPC codes. Moreover, our new method can avoid the computation of the inverse of the degree distribution function for irregular LDPC codes. Numerical results demonstrate the correctness of our proposed method.A simple method for determining the threshold of irregular LDPC codes over the binary erasure channel (BEC) under message-passing decoding is proposed. An exact formula for calculating the threshold of irregular LDPC codes over the BEC is proved. This generalizes the known result on the threshold of regular LDPC codes to irregular LDPC codes. Moreover, our new method can avoid the computation of the inverse of the degree distribution function for irregular LDPC codes. Numerical results demonstrate the correctness of our proposed method.

Progress in Natural Science Materials InternationalApr 29, 20091 citation

The Asymptotic Bit Error Probability of LDPC Codes for the Binary Erasure Channel with Finite Iteration Number

Ryuhei Mori, Kenta Kasai, Tomoharu Shibuya +1 more

We consider communication over the binary erasure channel (BEC) using low-density parity-check (LDPC) code and belief propagation (BP) decoding. The bit error probability for infinite block length is known by density evolution and it is well known that a difference between the bit error probability at finite iteration number for finite block length $n$ and for infinite block length is asymptotically $α/n$ , where $α$ is a specific constant depending on the degree distribution, the iteration number and the erasure probability. Our main result is to derive an efficient algorithm for calculating $α$ for regular ensembles. The approximation using $α$ is accurate for $(2,r)$ -regular ensembles even in small block length.We consider communication over the binary erasure channel (BEC) using low-density parity-check (LDPC) code and belief propagation (BP) decoding. The bit error probability for infinite block length is known by density evolution and it is well known that a difference between the bit error probability at finite iteration number for finite block length $n$ and for infinite block length is asymptotically $α/n$, where $α$ is a specific constant depending on the degree distribution, the iteration number and the erasure probability. Our main result is to derive an efficient algorithm for calculating $α$ for regular ensembles. The approximation using $α$ is accurate for $(2,r)$-regular ensembles even in small block length.

arXiv:0801.0931Jan 7, 20080 citations

n

and for infinite block length is asymptotically

α/n

, where

α

is a specific constant depending on the degree distribution, the iteration number and the erasure probability. Our main result is to derive an efficient algorithm for calculating

α

for regular ensembles. The approximation using

α

is accurate for

(2,r)

-regular ensembles even in small block length.