LAPSE:2023.25292
Published Article
LAPSE:2023.25292
PLC Physical Layer Link Identification with Imperfect Channel State Information
March 28, 2023
This paper proposes an accurate physical layer technique to uniquely identify the links of a power line communication network. First, the power line communications (PLC) multipath channel characterization is presented and detailed. Then, a multipath channel delay detection technique is introduced to provide an accurate physical layer identification (PL ID) for the considered PLC links. The accuracy and efficiency are tested by evaluating the successful path detection probability (SPDP) in a simulated scenario under both perfect and imperfect channel state information conditions. The results confirm the advantages of the proposed scheme. Indeed, for a common PLC noise power around 90 dBuV, the provided accuracy reaches ≈90%, while for a noise power below 80 dBuV, the accuracy plateaus at 100%. Overall, the low complexity of the proposed approach and its staggering performance results pave the way for further possible applications in both the PLC and the security domain.
Keywords
identification, physical layer security, PLC, smart grid
Suggested Citation
Hernandez Fernandez J, Omri A, Di Pietro R. PLC Physical Layer Link Identification with Imperfect Channel State Information. (2023). LAPSE:2023.25292
Author Affiliations
Hernandez Fernandez J: Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Doha P.O. Box 5825, Qatar; Iberdrola Innovation Middle East, Doha P.O. Box 210177, Qatar [ORCID]
Omri A: Iberdrola Innovation Middle East, Doha P.O. Box 210177, Qatar
Di Pietro R: Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Doha P.O. Box 5825, Qatar [ORCID]
Journal Name
Energies
Volume
15
Issue
16
First Page
6055
Year
2022
Publication Date
2022-08-21
Published Version
ISSN
1996-1073
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Original Submission
Other Meta
PII: en15166055, Publication Type: Journal Article
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LAPSE:2023.25292
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doi:10.3390/en15166055
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Mar 28, 2023
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CC BY 4.0
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Mar 28, 2023
 
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