Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/118969
Título: Comparison of clustering algorithms for data detection in Multispectral Camera Communication
Autores/as: Moreno, Daniel 
Majlesein, Behnaz 
Guerra Yanez, Victor 
Rufo Torres, Julio Francisco 
Rabadán Borges, José Alberto 
Pérez Jiménez, Rafael 
Clasificación UNESCO: 3325 Tecnología de las telecomunicaciones
Palabras clave: Clustering
Multispectral
Optical camera communication
Temperature effect
Fecha de publicación: 2022
Editor/a: Institute of Electrical and Electronics Engineers (IEEE) 
Conferencia: 4th West Asian Symposium on Optical and Millimeter-wave Wireless Communications (WASOWC 2022) 
Resumen: In this work, the performance of an optical camera communication (OCC) system is compared using several clus-tering algorithms in a cluster-based data detection approach. Furthermore, a multispectral camera is utilized to capture the thermally induced spectral variations in light-emitting diodes (LEDs). Thus, more than one channel can be attained from the same device. The results of this paper prove that using a clustering method can enhance the bit error rate (BER). Finally, different training sets were used to fit the clustering models underlining the impact on the system performance.
URI: http://hdl.handle.net/10553/118969
ISBN: 978-1-6654-0913-1
DOI: 10.1109/WASOWC54657.2022.9798432
Fuente: 4th West Asian Symposium on Optical and Millimeter-wave Wireless Communications (WASOWC 2022), p. 1-5
Colección:Actas de congresos
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