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

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Titel: Resource Allocation in Downlink VLC-NOMA Systems for Factory Automation Scenario.
Autoren: Ryu WJ; ICT Convergence Research Center, Kumoh National Institute of Technology, Gumi 39177, Gyeongbuk, Republic of Korea., Kim JW; ICT Convergence Research Center, Kumoh National Institute of Technology, Gumi 39177, Gyeongbuk, Republic of Korea., Kim DS; Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi 39177, Gyeongbuk, Republic of Korea.
Quelle: Sensors (Basel, Switzerland) [Sensors (Basel)] 2022 Dec 02; Vol. 22 (23). Date of Electronic Publication: 2022 Dec 02.
Publikationsart: Journal Article
Sprache: English
Info zur Zeitschrift: Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220 (Electronic) Linking ISSN: 14248220 NLM ISO Abbreviation: Sensors (Basel) Subsets: PubMed not MEDLINE; MEDLINE
Imprint Name(s): Original Publication: Basel, Switzerland : MDPI, c2000-
MeSH-Schlagworte: Resource Allocation* , Light*, Reproducibility of Results ; Automation ; Algorithms
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.
References: Opt Express. 2018 Jul 9;26(14):18131-18142. (PMID: 30114093)
Sensors (Basel). 2022 Feb 11;22(4):. (PMID: 35214296)
Contributed Indexing: Keywords: deep neural network (DNN); factory automation; non-orthogonal multiple access (NOMA); power allocation; reliability; user-pairing scheme; visible light communication (VLC)
Entry Date(s): Date Created: 20221211 Date Completed: 20221216 Latest Revision: 20221221
Update Code: 20250114
PubMed Central ID: PMC9739748
DOI: 10.3390/s22239407
PMID: 36502109
Datenbank: MEDLINE
Beschreibung
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.
ISSN:1424-8220
DOI:10.3390/s22239407