Evidence map›Paper›PMID 36502109›Full record

ArticleSensors (Basel, Switzerland)2022

Resource Allocation in Downlink VLC-NOMA Systems for Factory Automation Scenario.

Won-Jae Ryu, Jae-Woo Kim, Dong-Seong Kim

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Won-Jae RyuICT Convergence Research Center, Kumoh National Institute of Technology, Gumi 39177, Gyeongbuk, Republic of Korea.ORCID 0000-0003-1987-5969
Jae-Woo KimICT Convergence Research Center, Kumoh National Institute of Technology, Gumi 39177, Gyeongbuk, Republic of Korea.ORCID 0000-0002-2622-4219
Dong-Seong KimDepartment of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi 39177, Gyeongbuk, Republic of Korea.ORCID 0000-0002-2977-5964

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Industry 4.0 requires high-speed data exchange that includes fast, reliable, low-latency, and cost-effective data transmissions. As visible light communication (VLC) can provide reliable, low-latency, and secure connections that do not penetrate walls and are immune to electromagnetic interference; it can be considered a solution for Industry 4.0. The non-orthogonal multiple access (NOMA) technique can achieve high spectral efficiency using the same frequency and time resources for multiple users. It means that smaller amounts of resources will be used compared with orthogonal multiple access (OMA). Therefore, handling multiple data transmissions with VLC-NOMA can be easier for factory automation than OMA. However, as the transmit power is split, the reliability is reduced. Therefore, this study proposed a deep neural network (DNN)-based power-allocation algorithm (DBPA) to improve the reliability of the system. Further, to schedule multiple nodes in VLC-NOMA system, a priority-based user-pairing (PBUP) scheme is proposed. The proposed techniques in VLC-NOMA system were evaluated in terms of the factory automation scenario and showed that it improves reliability and reduces missed deadlines.

Indexed as

LightResource AllocationAlgorithmsAutomationReproducibility of Resultsdeep neural network (DNN)factory automationnon-orthogonal multiple access (NOMA)power allocationreliabilityuser-pairing schemevisible light communication (VLC)

Identifiers

PMID36502109
PMCPMC9739748

What OpenQuestion holds

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Registered trials

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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.