Peeling decoding of LDPC codes with applications in compressed sensing
type: Item
instance of: scholarly article
title: Peeling decoding of LDPC codes with applications in compressed sensing
zbMATH Open document ID: 1400.94076
DOI: 10.1155/2016/6340430
author: Weijun Zeng
author: Huali Wang
published in: Mathematical Problems in Engineering
publication date: 2018-10-12T00:00:00Z
review text: Summary: We present a new approach for the analysis of iterative peeling decoding recovery algorithms in the context of Low-Density Parity-Check (LDPC) codes and compressed sensing. The iterative recovery algorithm is particularly interesting for its low measurement cost and low computational complexity. The asymptotic analysis can track the evolution of the fraction of unrecovered signal elements in each iteration, which is similar to the well-known density evolution analysis in the context of LDPC decoding algorithm. Our analysis shows that there exists a threshold on the density factor; if under this threshold, the recovery algorithm is successful; otherwise it will fail. Simulation results are also provided for verifying the agreement between the proposed asymptotic analysis and recovery algorithm. Compared with existing works of peeling decoding algorithm, focusing on the failure probability of the recovery algorithm, our proposed approach gives accurate evolution of performance with different parameters of measurement matrices and is easy to implement. We also show that the peeling decoding algorithm performs better than other schemes based on LDPC codes.
Mathematics Subject Classification ID: 94A12
Mathematics Subject Classification ID: 94B35
Mathematics Subject Classification ID: 94A20
zbMATH DE Number: 6953430
Wikidata QID: Q59140868
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2016/6340430
OpenAlex ID: W2315483793
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description: scientific article; zbMATH DE number 6953430