Signal-to-Noise Ratio Enhancements Enabling 1.6-km Outdoor Visible Light Communication Using Vehicle Lights and Cameras
Light-based communications offer a promising alternative to alleviate congestion in crowded radio frequency bands and extend communication frequencies towards the THz range. This paper addresses the challenge of strong background interference in outdoor visible light communication (VLC) and presents...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11000125/ |
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| Summary: | Light-based communications offer a promising alternative to alleviate congestion in crowded radio frequency bands and extend communication frequencies towards the THz range. This paper addresses the challenge of strong background interference in outdoor visible light communication (VLC) and presents novel techniques to enable VLC using existing vehicle lights and cameras, focusing on physical layer enhancements for signal-to-noise ratio (SNR) improvement. These enhancements to commodity hardware-based VLC systems apply to vehicular communication, outdoor Internet-of-Things (IoT) devices, and mobile personal communications devices. New techniques, including preamble-based digital area filtering, optical magnification, and polarization filtering, are experimentally validated at distances up to 1650 m, demonstrating SNR improvements at unprecedented distances over four times farther than previously reported for outdoor VLC. Preamble-based digital area filtering across the camera sensor significantly improves SNR. Compact optical magnification increases both selectivity and array gain, providing over 10 dB of SNR gain at 1.6 km. Polarization filtering provides up to 4 dB of SNR gain even with an unpolarized signal source, and attenuating filters improve SNR at shorter ranges. These results demonstrate the viability of low-cost, long-distance VLC using commodity hardware and provide a foundation for future research on robust VLC for intelligent transportation systems and connected networks. |
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| ISSN: | 2169-3536 |