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

A Weighted Belief Propagation Decoding Algorithm of LDPC Codes for Fast Convergence and Early Stopping

Tso-Cho Chen

Published Jul 1, 2012• 0 citations
Publisher

Abstract

A weighted belief propagation decoding algorithm for low-density parity-check decoding is proposed to accelerate the convergence of decoding and reduce the number of decoding iterations. We propose an early stopping criterion which is based on the average weighted reliability measure of the hard output of decoder to detect undecodable blocks in an early stage of the decoding process. In addition, an adaptive weighted iteration scheme is proposed to increase the convergence speed of belief propagation (BP) decoding and therefore improve the error performance. The evolution of the adaptive weighting factor with the number of decoding iterations is based on the relative entropy between two consecutive ”a posteriori” probabilities distribution at decoder output. Simulation results show that the proposed algorithm can achieve about 0.2-0.4 dB coding gain improvement on average while reducing up to about 50%-85% iterations for decoding at low to medium E(subscript b)/ N(subscript 0) , compared with the conventional BP based algorithms.

DOI
10.7095/jcust.201207.0019

Related papers

A hybrid belief propagation decoding algorithms of LDPC codes for fast convergence

Tso-Cho Chen, Chia‐Jung Li, Erl‐Huei Lu

A hybrid belief propagation (BP) decoding algorithm for low-density parity-check code is proposed to accelerate the convergence of decoding and reduce the number of decoding iterations. The hybrid scheme is presented by integrating the BP algorithm with the bit-flipping function which is used as adaptive weighted factor in the BP iteration decoding. The adaptive weighting factor is based on the average weighted reliability measure of the hard output of decoder. The proposed hybrid adaptive weighted iteration scheme can efficiently increase the convergence speed of the belief propagation decoding and therefore improve the error performance. Simulation results show that the proposed algorithm can significantly reduce the decoding complexity and achieve better error performances as compared with the sum-product algorithm.

Cross Strait Radio Science and Wireless Technology Conference (CSRSWTC)•Jul 1, 2013•5 citations

An early stopping criterion for LDPC decoding based on average weighted reliability measure

Tso-Cho Chen

An early stopping criterion for low-density parity-check decoding is proposed to reduce the number of decoding iterations. The proposed early stopping criterion is based on the average weighted reliability measure of the hard output of decoder to detect undecodable blocks in an early stage of the decoding process. Simulation results show that the proposed algorithm can achieve about 0.2–0.4 dB coding gain improvement on average while reducing up to about 50%–85% iteration for decoding at low to medium Eb/N0, compared with the existing method.

Cross Strait Quad-Regional Radio Science and Wireless Technology Conference (CSQRWC)•Jul 1, 2012•2 citations

An Adaptive Algorithm and Stopping Criterion for LDPC Decoding

Tso-Cho Chen

A new adaptive and early stopping scheme for low-density parity-check (LDPC) decoding is proposed for accelerating the convergence of message-passing algorithms. The new algorithm is based on the cross-entropy between two consecutive a posteriori probabilities distribution of the soft output of decoder. Information-theoretic support and extensive simulations are provided to demonstrate the efficiency of the proposed adaptive algorithm and early stopping criterion. The proposed scheme can significantly reduce the average number of iterations of decoder while having a comparable or even better performance than conventional message-passing algorithms.

•Jul 1, 2011•0 citations

Adaptive decoding of LDPC codes based on cross-entropy

Tso-Cho Chen

An adaptive decoding scheme for low-density parity-check (LDPC) codes is proposed for accelerating the convergence of message-passing algorithms. The evolution of adaptive weighting factor with the number of decoding iterations and stopping criterion are based on the cross-entropy between two consecutive a posteriori probabilities distribution of the soft output of decoder. Information-theoretic support and extensive simulations are provided to demonstrate the efficiency of the proposed algorithm for LDPC decoding. The proposed adaptive decoding algorithm can reduce significantly the average number of iterations of decoder while having a comparable or even better performance than conventional message-passing algorithms.

Cross Strait Radio Science and Wireless Technology Conference (CSRSWTC)•Jul 1, 2011•0 citations

Improved belief propagation algorithm for decoding of convolutional LDPC codes

Chen Ru-wei

A novel belief propagation(BP) decoding algorithm for convolutional low-density parity-check codes is proposed.The proposed algorithm raises the efficiency of updating the variable information by applying feedback information at each decoding iteration and employs the weighting factor to reduce the error propagation caused by the cycles in the Tanner graph,thus yielding a faster convergence of the decoding.Simulation results show that an error performance better than that of the existing belief propagation algorithm can be achieved,while the 5/8 decoding delay and the computation complexity are effectively reduced.Compared with the existing BP,the proposed algorithm achieves a gain of 0.16dB at the BER of 10-6 with the same number of iterations.

Journal of Xidian University•Jan 1, 2009•0 citations

Iterative reliability-based decoding of low-density parity check codes

M.P.C. Fossorier

In this paper, reliability based decoding is combined with belief propagation (BP) decoding for low-density parity check (LDPC) codes. At each iteration, the soft output values delivered by the BP algorithm are used as reliability values to perform reduced complexity soft decision decoding of the code considered. This approach allows to bridge the error performance gap between belief propagation decoding which remains suboptimum, and maximum likelihood decoding which is too complex to be implemented for the codes considered. Trade-offs between decoding complexity and error performance are also investigated. In particular, a stopping criterion which reduces the average number of iterations at the expense of very little performance degradation is proposed for this combined decoding approach. Simulation results for several Gallager (1963, 1968) LDPC codes and different set cyclic codes of hundreds of information bits are given and elaborated.

IEEE Journal on Selected Areas in Communications•May 1, 2001•167 citations
A weighted belief propagation decoding algorithm for low-density parity-check decoding is proposed to accelerate the convergence of decoding and reduce the number of decoding iterations. We propose an early stopping criterion which is based on the average weighted reliability measure of the hard output of decoder to detect undecodable blocks in an early stage of the decoding process. In addition, an adaptive weighted iteration scheme is proposed to increase the convergence speed of belief propagation (BP) decoding and therefore improve the error performance. The evolution of the adaptive weighting factor with the number of decoding iterations is based on the relative entropy between two consecutive ”a posteriori” probabilities distribution at decoder output. Simulation results show that the proposed algorithm can achieve about 0.2-0.4 dB coding gain improvement on average while reducing up to about 50%-85% iterations for decoding at low to medium E(subscript b)/ N(subscript 0) , compared with the conventional BP based algorithms.
A hybrid belief propagation (BP) decoding algorithm for low-density parity-check code is proposed to accelerate the convergence of decoding and reduce the number of decoding iterations. The hybrid scheme is presented by integrating the BP algorithm with the bit-flipping function which is used as adaptive weighted factor in the BP iteration decoding. The adaptive weighting factor is based on the average weighted reliability measure of the hard output of decoder. The proposed hybrid adaptive weighted iteration scheme can efficiently increase the convergence speed of the belief propagation decoding and therefore improve the error performance. Simulation results show that the proposed algorithm can significantly reduce the decoding complexity and achieve better error performances as compared with the sum-product algorithm.
An early stopping criterion for low-density parity-check decoding is proposed to reduce the number of decoding iterations. The proposed early stopping criterion is based on the average weighted reliability measure of the hard output of decoder to detect undecodable blocks in an early stage of the decoding process. Simulation results show that the proposed algorithm can achieve about 0.2–0.4 dB coding gain improvement on average while reducing up to about 50%–85% iteration for decoding at low to medium Eb/N0, compared with the existing method.
A new adaptive and early stopping scheme for low-density parity-check (LDPC) decoding is proposed for accelerating the convergence of message-passing algorithms. The new algorithm is based on the cross-entropy between two consecutive a posteriori probabilities distribution of the soft output of decoder. Information-theoretic support and extensive simulations are provided to demonstrate the efficiency of the proposed adaptive algorithm and early stopping criterion. The proposed scheme can significantly reduce the average number of iterations of decoder while having a comparable or even better performance than conventional message-passing algorithms.
An adaptive decoding scheme for low-density parity-check (LDPC) codes is proposed for accelerating the convergence of message-passing algorithms. The evolution of adaptive weighting factor with the number of decoding iterations and stopping criterion are based on the cross-entropy between two consecutive a posteriori probabilities distribution of the soft output of decoder. Information-theoretic support and extensive simulations are provided to demonstrate the efficiency of the proposed algorithm for LDPC decoding. The proposed adaptive decoding algorithm can reduce significantly the average number of iterations of decoder while having a comparable or even better performance than conventional message-passing algorithms.
A novel belief propagation(BP) decoding algorithm for convolutional low-density parity-check codes is proposed.The proposed algorithm raises the efficiency of updating the variable information by applying feedback information at each decoding iteration and employs the weighting factor to reduce the error propagation caused by the cycles in the Tanner graph,thus yielding a faster convergence of the decoding.Simulation results show that an error performance better than that of the existing belief propagation algorithm can be achieved,while the 5/8 decoding delay and the computation complexity are effectively reduced.Compared with the existing BP,the proposed algorithm achieves a gain of 0.16dB at the BER of 10-6 with the same number of iterations.
In this paper, reliability based decoding is combined with belief propagation (BP) decoding for low-density parity check (LDPC) codes. At each iteration, the soft output values delivered by the BP algorithm are used as reliability values to perform reduced complexity soft decision decoding of the code considered. This approach allows to bridge the error performance gap between belief propagation decoding which remains suboptimum, and maximum likelihood decoding which is too complex to be implemented for the codes considered. Trade-offs between decoding complexity and error performance are also investigated. In particular, a stopping criterion which reduces the average number of iterations at the expense of very little performance degradation is proposed for this combined decoding approach. Simulation results for several Gallager (1963, 1968) LDPC codes and different set cyclic codes of hundreds of information bits are given and elaborated.