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IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
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The innovation of touch-tone telephony revolutionized the telecommunications industry by replacing the traditional rotary dial with a dual-tone multi-frequency (DTMF) signaling system. This system uses a matrix-style keypad with buttons arranged in four rows and three columns, creating 12 distinct signals each assigned to a pair of frequencies. Each button press results in a simultaneous generation of two sinusoidal tones – one from a low-frequency group (697 to 941 Hz) and one from a...
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Updated: Nov 15, 2025

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On Improving 5G Internet of Radio Light Security Based on LED Fingerprint Identification Method.

Dayu Shi1, Xun Zhang1, Lina Shi1

  • 1Laboratory LISITE, Institut Supérieur D'électronique de Paris, 75006 Paris, France.

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|March 6, 2021
PubMed
Summary

This study introduces a new method for identifying devices in Visible Light Communication (VLC) 5G networks by extracting unique Light-Emitting Diode (LED) fingerprints. This approach achieves high accuracy, enhancing network security.

Keywords:
5G networksLED fingerprintsecurityvisible light communication

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Area of Science:

  • Communications Engineering
  • Cybersecurity
  • Optical Networking

Background:

  • Visible Light Communication (VLC) offers a promising high-speed wireless technology for 5G networks.
  • Ensuring device security and identification is crucial for the reliable deployment of VLC in 5G infrastructure.
  • Existing identification methods may not fully leverage the unique characteristics of VLC hardware.

Purpose of the Study:

  • To propose and validate a novel device identification method for VLC-enabled 5G networks.
  • To enhance the security of 5G networks utilizing Visible Light Communication.
  • To investigate the feasibility and accuracy of LED fingerprinting for device identification.

Main Methods:

  • Extraction of unique Light-Emitting Diode (LED) fingerprints from received 5G New Radio (NR) signals.
  • Theoretical analysis and experimental verification of fingerprint extraction and identification mechanisms.
  • Implementation and evaluation in a practical indoor VLC-based 5G network environment.

Main Results:

  • Successful extraction of distinct fingerprints from four identical white LEDs.
  • Machine learning classifiers achieved up to 97.1% accuracy in identifying devices based on LED fingerprints.
  • Demonstrated the practical feasibility and high accuracy of the proposed identification method.

Conclusions:

  • LED fingerprinting is a viable and effective method for device identification in VLC 5G networks.
  • The proposed method significantly enhances the security of 5G networks employing Visible Light Communication.
  • This technique offers a robust solution for authenticating devices within VLC-based communication systems.