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

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00376552" target="_blank" >RIV/68407700:21230/24:00376552 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/CSNDSP60683.2024.10636560" target="_blank" >https://doi.org/10.1109/CSNDSP60683.2024.10636560</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CSNDSP60683.2024.10636560" target="_blank" >10.1109/CSNDSP60683.2024.10636560</a>

Result language
angličtina
Original language name
Machine Learning-Based Channel Allocation for Secure Indoor Visible Light Communications
Original language description
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.
Czech name
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Czech description
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Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 14th International Symposium on Communication Systems, Networks and Digital Signal Processing
ISBN
979-8-3503-4874-3
ISSN
—
e-ISSN
—
Number of pages
6
Pages from-to
506-511
Publisher name
IEEE
Place of publication
—
Event location
Rome
Event date
Jul 17, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001324588800096

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