Rolling-shutter-effect camera-based visible light communication using RGB channel separation and an artificial neural...

Area of Science:

• Optoelectronics
• Communication Systems
• Machine Learning

Background:

• Visible Light Communication (VLC) systems offer high-speed wireless data transmission.
• Rolling-shutter-effect (RSE) cameras introduce inter-symbol interference (ISI) in VLC systems.
• Low pixel-per-bit and high noise-ratio (NR) challenges limit display-based VLC performance.

Purpose of the Study:

• To propose and demonstrate a novel VLC system mitigating RSE-induced ISI.
• To enhance data transmission reliability in display-based VLC.
• To address challenges of low pixel-per-bit and high NR in display contents.

Main Methods:

• Utilized a light-panel and RSE camera setup.
• Implemented Z-score normalization for data preprocessing.
• Employed red/green/blue (RGB) color channel separation.
• Applied a 1-D artificial neural network (ANN) for signal processing.

Main Results:

• Successfully mitigated high inter-symbol interference (ISI) caused by RSE patterns.
• Demonstrated improved data transmission quality despite low pixel-per-bit and high NR.
• Validated the effectiveness of the proposed Z-score normalization, RGB separation, and ANN approach.

Conclusions:

• The proposed light-panel and RSE camera VLC system effectively overcomes RSE-induced ISI.
• The integration of Z-score normalization, RGB channel separation, and ANN provides a robust solution for display-based VLC.
• This approach enhances the feasibility and performance of VLC systems in challenging display environments.