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

International Conference on Wireless Communications, Networking and Mobile Computing

Optimization of irregular LDPC codes on rician channel

Hua Xu, Chengqi Xu, Xiao-chuan Zhang

Published Dec 10, 2005• 2 citations
Publisher

Abstract

For irregular LDPC codes,the density evolution method can track the messages to find out the noise threshold, enabling optimization of the degree distribution. A new optimized scheme for irregular LDPC codes is proposed in this paper, which is combining Zhengya He's modified particle swarm optimization (PSO) algorithm with discrete density evolution (DDE) for the offset BP-based decoding algorithm. Several optimized degree distribution pairs and corresponding threshold of LDPC codes over Rician channel were given using the proposed scheme. The performance of the optimized LDPC codes was also analyzed. Simulation results shows that the proposed scheme is effective.

DOI
10.1109/wcnm.2005.1544061

Related papers

Research of Density Evolution of LDPC Codes over Rice Channels

Hua Xu, Chengqi Xu

Noise threshold of Low Density Parity Check (LDPC) codes ensemble could be calculated by density evolution of the decoding messages. According to the threshold, performance of the decoding algorithm could be evaluated and degree distribution pairs of irregular LDPC codes also might be optimized. In this paper, for regular LDPC codes on Rice channel, Discrete Density Evolution(DDE) for BP,BP-based and offset BP-based decoding algorithm were compared on different quantization level and step. Furthermore, degree distribution pairs of the irregular LDPC codes were optimized on Rice channel, which was based on DDE for offset BP-based decoding algorithm, the corresponding threshold is also calculated. Finally, the Probability Mass Function (PMF) evolution curve of optimized irregular LDPC codes with code rate 1/2 on Rice channel is given.

JOURNAL OF ELECTRONICS INFORMATION TECHNOLOGY•Oct 19, 2006•0 citations

Research of Fixed Point of LDPC Decoding over Rice Channel

Chengqi Xu

Research of the fixed point which appears in decoding process of LDPC codes is important to further analyze the decoding mechanism and speed up decoding convergence.Firstly,a new optimization scheme which combines DDE(Discrete Density Evolution)for offset BP-based decoding algorithm with differential evolution is presented for optimizing irregular LDPC codes.Then the optimized degree distribution pair and threshold of LDPC codes over Rice channel are given,with the maximum bit node degree 10 and code rate R=1/2,1/3.Furthermore,we analyze a series of simulated curves related to LDPC decoding fixed point and threshold phenomenon.Simulation results show that the node with higher degree contributes more to the decoding for LDPC codes.Therefore,we tentatively put forward two kinds of thinking to improve LDPC decoding algorithm.

Journal of Nanjing University of Posts and Telecommunications•Jan 1, 2007•0 citations

Density evolution method and threshold decision for irregular LDPC codes

Lin Wang, Juan Xiao, Guanrong Chen

Density evolution is a new method for analyzing the asymptotic performance of network capability approaching error-correcting codes. For irregular LDPC codes with message-passing decoding, the density evolution method can track the messages to find out the threshold, enabling optimization of the degree distribution. In this paper, the principle of density evolution combined with the decoding process is firstly explored. Then, two algorithms for programming the evolution proceeding are discussed: the discretized density evolution and the Gaussian approximation, as well as their application conditions. Finally, simulation results are presented.

International Conference on Communications, Circuits and Systems•Jan 1, 2004•10 citations

Discrete density evolution and LDPC codes designwith asymmetric channels

涛 袁, 征 马, 琦珂 庞 +1 more

To design low-density parity-check (LDPC) codes with asymmetric channels and analyze their performance, an achievable asymmetric discrete density evolution method is proposed, which is based on offset min-sum decoding. First, the iterative formula of low-complexity asymmetric channel discrete density evolution is derived by means of combinatorics, difference method and the binomial theorem. The iterative formula is applied to further optimize the design of the LDPC codes using the offset min-sum decoding, and the optimal degree distributions and performance of the LDPC codes under different quantization ranges and step sizes are obtained under the asymmetric channel. Finally, the optimal offset values under high-precision quantization are obtained. The results show that under the asymmetric channel, the complexity of the proposed asymmetric density evolution method based on the offset min-sum decoding is reduced by an order of magnitude than that using the original method. For a fixed code rate, the smaller the variable node degree of the regular codes, the better the performance and the smaller the optimal offset value. For irregular LDPC codes, the optimal degree distributions and offset values are determined according to the differential evolution algorithm. For a fixed code rate, the larger the maximum variable node degree, the better the performance of irregular codes.

Scientia Sinica Informationis•Aug 29, 2022•1 citation

Designing near Shannon limit LDPC codes using particle swarm optimization algorithm

Fatma A. Newagy, Yasmine A. H. Fahmy, Magdi S. El-Soudani

This paper presents a new design methodology/process for low-density parity-check codes (LDPC). To minimize the gap to Shannon limit, the particle swarm optimizer is applied to optimize the variable and check node degree distribution lambda and p respectively in case of irregular LDPC codes. discrete fast density evolution (FDE) is used (as the analysis technique) to compute the threshold value of LDPC code and the Shannon limit is evaluated based on Butman and McEliece formula. The results conducted show that, our proposed distributions with low degrees of (lambda, p) outperform other comparable distributions.

International Conference on Telecommunications•Jan 1, 2007•5 citations

Design of degree sequence for irregular LDPC codes on PSO

Linhua Ma

The algorithm of threshold calculation for low-density parity-check(LDPC) codes is investigated.The design steps of degree-sequence which has higher threshold and the process of constrained problem are discussed in detail.A method of degree-sequence design for LDPC on particle swarm optimization(PSO) is presented.The analysis and comparison of estimation result and some capacity-approaching degree-sequences are also given.

Systems engineering and electronics•Jan 1, 2010•0 citations
For irregular LDPC codes,the density evolution method can track the messages to find out the noise threshold, enabling optimization of the degree distribution. A new optimized scheme for irregular LDPC codes is proposed in this paper, which is combining Zhengya He's modified particle swarm optimization (PSO) algorithm with discrete density evolution (DDE) for the offset BP-based decoding algorithm. Several optimized degree distribution pairs and corresponding threshold of LDPC codes over Rician channel were given using the proposed scheme. The performance of the optimized LDPC codes was also analyzed. Simulation results shows that the proposed scheme is effective.
Noise threshold of Low Density Parity Check (LDPC) codes ensemble could be calculated by density evolution of the decoding messages. According to the threshold, performance of the decoding algorithm could be evaluated and degree distribution pairs of irregular LDPC codes also might be optimized. In this paper, for regular LDPC codes on Rice channel, Discrete Density Evolution(DDE) for BP,BP-based and offset BP-based decoding algorithm were compared on different quantization level and step. Furthermore, degree distribution pairs of the irregular LDPC codes were optimized on Rice channel, which was based on DDE for offset BP-based decoding algorithm, the corresponding threshold is also calculated. Finally, the Probability Mass Function (PMF) evolution curve of optimized irregular LDPC codes with code rate 1/2 on Rice channel is given.
Research of the fixed point which appears in decoding process of LDPC codes is important to further analyze the decoding mechanism and speed up decoding convergence.Firstly,a new optimization scheme which combines DDE(Discrete Density Evolution)for offset BP-based decoding algorithm with differential evolution is presented for optimizing irregular LDPC codes.Then the optimized degree distribution pair and threshold of LDPC codes over Rice channel are given,with the maximum bit node degree 10 and code rate R=1/2,1/3.Furthermore,we analyze a series of simulated curves related to LDPC decoding fixed point and threshold phenomenon.Simulation results show that the node with higher degree contributes more to the decoding for LDPC codes.Therefore,we tentatively put forward two kinds of thinking to improve LDPC decoding algorithm.
Density evolution is a new method for analyzing the asymptotic performance of network capability approaching error-correcting codes. For irregular LDPC codes with message-passing decoding, the density evolution method can track the messages to find out the threshold, enabling optimization of the degree distribution. In this paper, the principle of density evolution combined with the decoding process is firstly explored. Then, two algorithms for programming the evolution proceeding are discussed: the discretized density evolution and the Gaussian approximation, as well as their application conditions. Finally, simulation results are presented.
To design low-density parity-check (LDPC) codes with asymmetric channels and analyze their performance, an achievable asymmetric discrete density evolution method is proposed, which is based on offset min-sum decoding. First, the iterative formula of low-complexity asymmetric channel discrete density evolution is derived by means of combinatorics, difference method and the binomial theorem. The iterative formula is applied to further optimize the design of the LDPC codes using the offset min-sum decoding, and the optimal degree distributions and performance of the LDPC codes under different quantization ranges and step sizes are obtained under the asymmetric channel. Finally, the optimal offset values under high-precision quantization are obtained. The results show that under the asymmetric channel, the complexity of the proposed asymmetric density evolution method based on the offset min-sum decoding is reduced by an order of magnitude than that using the original method. For a fixed code rate, the smaller the variable node degree of the regular codes, the better the performance and the smaller the optimal offset value. For irregular LDPC codes, the optimal degree distributions and offset values are determined according to the differential evolution algorithm. For a fixed code rate, the larger the maximum variable node degree, the better the performance of irregular codes.
This paper presents a new design methodology/process for low-density parity-check codes (LDPC). To minimize the gap to Shannon limit, the particle swarm optimizer is applied to optimize the variable and check node degree distribution lambda and p respectively in case of irregular LDPC codes. discrete fast density evolution (FDE) is used (as the analysis technique) to compute the threshold value of LDPC code and the Shannon limit is evaluated based on Butman and McEliece formula. The results conducted show that, our proposed distributions with low degrees of (lambda, p) outperform other comparable distributions.