Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Problems of Information Transmission

Decoding of low-density codes with parity-check matrices composed of permutation matrices in an erasure channel

D. K. Zigangirov, Kamil Sh. Zigangirov

Published Jun 1, 2006• 4 citations
Publisher

Abstract

A lower bound for the number of iteratively correctable erasures is given, with application to the ensemble of LDPC codes with parity-check matrices composed of permutation matrices [1]. We assume that the Zyablov-Pinsker iterative decoding algorithm [2] is used. Its complexity is O ( N log N ), where N is the block length.
DOI
10.1134/s0032946006020049

Related papers

On the Erasure Correction Capability of LDPC Codes

D. K. Zigangirov, Kamil Sh. Zigangirov

The erasure correcting capability of LDPC codes with parity-check matrices composed of permutation matrices is considered. A new lower bound for number of the iteratively correcting erasures for the Zyablov-Pinsker algorithm is given

IEEE International Symposium on Information Theory (ISIT)•Jul 1, 2006•0 citations

On the error-correcting capability of LDPC codes

Kamil Sh. Zigangirov, A. E. Pusane, D. K. Zigangirov +1 more

We consider the ensemble of low-density parity-check (LDPC) codes introduced by Gallager [1]. The Zyablov-Pinsker majority-logic iterative algorithm [2] for decoding LDPC codes is analyzed on the binary symmetric channel. An analytical lower bound on the error-correcting capability τ max that grows linearly in the code block length is obtained.

Problems of Information Transmission•Sep 1, 2008•11 citations

Erasure correction by low-density codes

Victor Zyablov, Pavel S. Rybin

We generalize the method for computing the number of errors correctable by a low-density parity-check (LDPC) code in a binary symmetric channel, which was proposed by V.V. Zyablov and M.S. Pinsker in 1975. This method is for the first time applied for computing the fraction of guaranteed correctable erasures for an LDPC code with a given constituent code used in an erasure channel. Unlike previously known combinatorial methods for computing the fraction of correctable erasures, this method is based on the theory of generating functions, which allows us to obtain more precise results and unify the computation method for various constituent codes of a regular LDPC code. We also show that there exist an LDPC code with a given constituent code which, when decoded with a low-complexity iterative algorithm, is capable of correcting any erasure pattern with a number of erasures that grows linearly with the code length. The number of decoding iterations, required to correct the erasures, is a logarithmic function of the code length. We make comparative analysis of various numerical results obtained by various computation methods for certain parameters of an LDPC code with a constituent single-parity-check or Hamming code.

Problems of Information Transmission•Sep 1, 2009•6 citations

On the erasure-correcting capabilities of low-complexity decoded LDPC codes with constituent Hamming codes

Victor Zyablov, Maja Lončar, Rolf Johannesson +1 more

Low-density parity-check (LDPC) codes can be constructed using constituent block codes other than single parity-check (SPC) codes. This paper considers random LDPC codes with constituent Hamming codes and investigates their asymptotic performance over the binary erasure channel. It is shown that there exist Hamming code-based LDPC codes which, when decoded with a low-complexity iterative algorithm, are capable of correcting any erasure pattern with a number of erasures that grows linearly with the code length. The number of decoding iterations, required to correct the erasures, is a logarithmic function of the code length. The fraction of correctable erasures is computed numerically for various choices of code parameters.

•Jan 1, 2008•6 citations

Finite-length analysis of low-density parity-check codes on the binary erasure channel

Changyan Di, D. Proietti, I. Emre Telatar +2 more

In this paper, we are concerned with the finite-length analysis of low-density parity-check (LDPC) codes when used over the binary erasure channel (BEC). The main result is an expression for the exact average bit and block erasure probability for a given regular ensemble of LDPC codes when decoded iteratively. We also give expressions for upper bounds on the average bit and block erasure probability for regular LDPC ensembles and the standard random ensemble under maximum-likelihood (ML) decoding. Finally, we present what we consider to be the most important open problems in this area.

IEEE Transactions on Information Theory•Jun 1, 2002•864 citations

On Decoding of Low-Density Parity-Check Codes Over the Binary Erasure Channel

Hossein Pishro-Nik, Faramarz Fekri

This paper investigates decoding of low-density parity-check (LDPC) codes over the binary erasure channel (BEC). We study the iterative and maximum-likelihood (ML) decoding of LDPC codes on this channel. We derive bounds on the ML decoding of LDPC codes on the BEC. We then present an improved decoding algorithm. The proposed algorithm has almost the same complexity as the standard iterative decoding. However, it has better performance. Simulations show that we can decrease the error rate by several orders of magnitude using the proposed algorithm. We also provide some graph-theoretic properties of different decoding algorithms of LDPC codes over the BEC which we think are useful to better understand the LDPC decoding methods, in particular, for finite-length codes.

IEEE Transactions on Information Theory•Mar 1, 2004•147 citations
We generalize the method for computing the number of errors correctable by a low-density parity-check (LDPC) code in a binary symmetric channel, which was proposed by V.V. Zyablov and M.S. Pinsker in 1975. This method is for the first time applied for computing the fraction of guaranteed correctable erasures for an LDPC code with a given constituent code used in an erasure channel. Unlike previously known combinatorial methods for computing the fraction of correctable erasures, this method is based on the theory of generating functions, which allows us to obtain more precise results and unify the computation method for various constituent codes of a regular LDPC code. We also show that there exist an LDPC code with a given constituent code which, when decoded with a low-complexity iterative algorithm, is capable of correcting any erasure pattern with a number of erasures that grows linearly with the code length. The number of decoding iterations, required to correct the erasures, is a logarithmic function of the code length. We make comparative analysis of various numerical results obtained by various computation methods for certain parameters of an LDPC code with a constituent single-parity-check or Hamming code.
Low-density parity-check (LDPC) codes can be constructed using constituent block codes other than single parity-check (SPC) codes. This paper considers random LDPC codes with constituent Hamming codes and investigates their asymptotic performance over the binary erasure channel. It is shown that there exist Hamming code-based LDPC codes which, when decoded with a low-complexity iterative algorithm, are capable of correcting any erasure pattern with a number of erasures that grows linearly with the code length. The number of decoding iterations, required to correct the erasures, is a logarithmic function of the code length. The fraction of correctable erasures is computed numerically for various choices of code parameters.
In this paper, we are concerned with the finite-length analysis of low-density parity-check (LDPC) codes when used over the binary erasure channel (BEC). The main result is an expression for the exact average bit and block erasure probability for a given regular ensemble of LDPC codes when decoded iteratively. We also give expressions for upper bounds on the average bit and block erasure probability for regular LDPC ensembles and the standard random ensemble under maximum-likelihood (ML) decoding. Finally, we present what we consider to be the most important open problems in this area.
This paper investigates decoding of low-density parity-check (LDPC) codes over the binary erasure channel (BEC). We study the iterative and maximum-likelihood (ML) decoding of LDPC codes on this channel. We derive bounds on the ML decoding of LDPC codes on the BEC. We then present an improved decoding algorithm. The proposed algorithm has almost the same complexity as the standard iterative decoding. However, it has better performance. Simulations show that we can decrease the error rate by several orders of magnitude using the proposed algorithm. We also provide some graph-theoretic properties of different decoding algorithms of LDPC codes over the BEC which we think are useful to better understand the LDPC decoding methods, in particular, for finite-length codes.