PMID- 36502109
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20221216
LR  - 20221221
IS  - 1424-8220 (Electronic)
IS  - 1424-8220 (Linking)
VI  - 22
IP  - 23
DP  - 2022 Dec 2
TI  - Resource Allocation in Downlink VLC-NOMA Systems for Factory Automation Scenario.
LID - 10.3390/s22239407 [doi]
LID - 9407
AB  - 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.
FAU - Ryu, Won-Jae
AU  - Ryu WJ
AUID- ORCID: 0000-0003-1987-5969
AD  - ICT Convergence Research Center, Kumoh National Institute of Technology, Gumi 
      39177, Gyeongbuk, Republic of Korea.
FAU - Kim, Jae-Woo
AU  - Kim JW
AUID- ORCID: 0000-0002-2622-4219
AD  - ICT Convergence Research Center, Kumoh National Institute of Technology, Gumi 
      39177, Gyeongbuk, Republic of Korea.
FAU - Kim, Dong-Seong
AU  - Kim DS
AUID- ORCID: 0000-0002-2977-5964
AD  - Department of IT Convergence Engineering, Kumoh National Institute of Technology, 
      Gumi 39177, Gyeongbuk, Republic of Korea.
LA  - eng
PT  - Journal Article
DEP - 20221202
PL  - Switzerland
TA  - Sensors (Basel)
JT  - Sensors (Basel, Switzerland)
JID - 101204366
SB  - IM
MH  - Reproducibility of Results
MH  - Automation
MH  - *Resource Allocation
MH  - *Light
MH  - Algorithms
PMC - PMC9739748
OTO - NOTNLM
OT  - deep neural network (DNN)
OT  - factory automation
OT  - non-orthogonal multiple access (NOMA)
OT  - power allocation
OT  - reliability
OT  - user-pairing scheme
OT  - visible light communication (VLC)
COIS- The authors declare no conflict of interest.
EDAT- 2022/12/12 06:00
MHDA- 2022/12/12 06:01
PMCR- 2022/12/02
CRDT- 2022/12/11 01:38
PHST- 2022/10/27 00:00 [received]
PHST- 2022/11/30 00:00 [revised]
PHST- 2022/11/30 00:00 [accepted]
PHST- 2022/12/11 01:38 [entrez]
PHST- 2022/12/12 06:00 [pubmed]
PHST- 2022/12/12 06:01 [medline]
PHST- 2022/12/02 00:00 [pmc-release]
AID - s22239407 [pii]
AID - sensors-22-09407 [pii]
AID - 10.3390/s22239407 [doi]
PST - epublish
SO  - Sensors (Basel). 2022 Dec 2;22(23):9407. doi: 10.3390/s22239407.