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Machine Learning-Based Channel Allocation for Secure Indoor Visible Light Communications | IEEE Conference Publication | IEEE Xplore

Machine Learning-Based Channel Allocation for Secure Indoor Visible Light Communications


Abstract:

In this paper, a machine learning (ML)-based channel allocation algorithm is proposed to form a secure communication zone in indoor visible light communication (VLC) syst...Show More

Abstract:

In this paper, a machine learning (ML)-based channel allocation algorithm is proposed to form a secure communication zone in indoor visible light communication (VLC) systems. The algorithm first employs the probabilistic neural network (PNN), which classifies the VLC transmitter (Tx) based on its proximity to the user's location. Subsequently, the selected Tx is used to establish a point-to-point channel allocation, hence forming a closed-access zone within a certain effective communication range. Through numerical simulations, it is observed that the single Tx-based VLC transmission confines the legitimate user in a pre-defined trust boundary for a secure transmission.
Date of Conference: 17-19 July 2024
Date Added to IEEE Xplore: 23 August 2024
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Conference Location: Rome, Italy

References

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