Evidence map›Paper›PMID 33809154›Full record

ArticleSensors (Basel, Switzerland)2021

Constructing LDPC Codes with Any Desired Girth.

Chaohui Gao, Sen Liu, Dong Jiang, Lijun Chen

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Chaohui GaoState Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210046, China.ORCID 0000-0001-7771-7809
Sen LiuState Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210046, China.
Dong JiangState Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210046, China.
Lijun ChenState Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210046, China.

Funding

Major Program of National Natural Science Foundation of China 11690030, 11690032National Key Research and Development Program of China 2017YFA0303704National Natural Science Foundation of China 61771236Natural Science Foundation of Jiangsu Province BK20190297
6 · The paper itself

Abstract

In wireless sensor networks, the reliability of communication can be greatly improved by applying low-density parity-check (LDPC) codes. Algorithms based on progressive-edge-growth (PEG) pattern and quasi-cyclic (QC) pattern are the mainstream approaches to constructing LDPC codes with good performance. However, these algorithms are not guaranteed to remove all short cycles to achieve the desired girth, and their excellent inputs are difficult to obtain. Herein, we propose an algorithm, which must be able to construct LDPC codes with the girth desired. In addition, the optimal input to the proposed algorithm is easy to find. Theoretical and experimental evidence of this study shows that the LDPC codes we construct have better decoding performance and less power consumption than the PEG-based and QC-based codes.

Indexed as

decodingerror correction codeLDPC code

Identifiers

PMID33809154
PMCPMC8000767

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.