Paper Info
Title
Improved Decoding Algorithms of LDPC Codes Based on Reliability Metrics of Variable Nodes.
Abstract
The informed dynamic scheduling (IDS) strategies for decoding of low-density parity-check codes obtained superior performance in error correction performance and convergence speed. However, there are still two problems existing in the current IDS algorithms. The first is that the current IDS algorithms only preferentially update the selected unreliable messages, but they do not guarantee the updating is performed with reliable information. In this paper, a two-step message selecting strategy is introduced. On the basis of the two reliability metrics and two types of variable node residuals, the residual belief propagation (BP) decoding algorithm, short for TRM-TVRBP, is proposed. With the algorithm, the reliability of the updating-messages can be improved. The second is the greediness problem, prevalently existed in the IDS-like algorithms. The problem arises mainly from the fact that the major computing resources are allocated to or concentrated on some nodes and edges. To overcome the problem, the reliability metric-based RBP algorithm (RM-RBP) is proposed, which can force every variable node to contribute its intrinsic information to the iterative decoding. At the same time, the algorithm can force the related variable nodes to be updated, and make every edge have an equal opportunity of being updated. The simulation results show that both the TRM-TVRBP and the RM-RBP have appealing convergence rate and error-correcting performance compared with the previous IDS decoders over the white Gaussian noise (AWGN) channel.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2904173
IEEE ACCESS
Keywords
Field
DocType
Low-density parity-check (LDPC) codes,dynamic selection strategies,dynamic updating strategies,residuals of variable nodes
Convergence (routing),Low-density parity-check code,Computer science,Algorithm,Communication channel,Error detection and correction,Rate of convergence,Decoding methods,Dynamic priority scheduling,Additive white Gaussian noise
Journal
Volume
ISSN
Citations 
7
2169-3536
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Xingcheng Liu16617.47
Li'e Zi200.34
Dong Yang311618.09
Zhongfeng Wang410.69