Hybrid RF-VLC Communication System: Performance Analysis and Deep Learning Detection in the Presence of Blockages

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dc.contributor.authorShaik, Parvez
dc.contributor.authorKeçeci, Cihat
dc.contributor.authorGarg, Kamal K.
dc.contributor.authorBoyacı, Ali
dc.contributor.authorIsmail, Muhammad
dc.contributor.authorSerpedin, Erchin
dc.date.accessioned2024-07-23T13:39:23Z
dc.date.available2024-07-23T13:39:23Z
dc.date.issued2024en_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractThis paper analyzes the performance of a dual-hop hybrid radio frequency - visible light communications (VLCs) system. VLC exploits high frequencies for signal propagation for short-range and is highly susceptible to blockages. Hence, in this work, the sensitivity of the VLC toward the blockages is explored. This study examines outdoor-indoor communication for an urban scenario featuring an office environment. The VLC system is designed by considering multiple VLC access points serving the end users in the presence of human blockages. Selection combining is employed to select the access point which offers the maximum instantaneous signal-to-noise ratio at the user. To capture the outdoor scenario, path loss modeling is conducted to account for signal attenuation from outdoor to indoor spaces. The outdoor scenario is modeled using Nakagami-m fading channels while VLC is employed for the indoor scenario. System performance is assessed in closed-form expression for outage probability and the symbol error rate for binary phase shift keying and quadrature amplitude modulation. A deep learning-based approach detects the symbols by tracking dynamic changes in the channel. Simulation results corroborate the correctness of derived analytical expressions and reveal that blockages significantly impact both single and multiple LED based communication channels.en_US
dc.identifier.doi10.1109/TVT.2024.3425729en_US
dc.identifier.endpage15en_US
dc.identifier.scopus2-s2.0-85198239859en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage1en_US
dc.identifier.urihttps://hdl.handle.net/11467/7378
dc.identifier.urihttps://doi.org/10.1109/TVT.2024.3425729
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofIEEE Transactions on Vehicular Technologyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.subjectDeep learning, Nakgami-m, VLC, Blockage, BPSK, and QAMen_US
dc.titleHybrid RF-VLC Communication System: Performance Analysis and Deep Learning Detection in the Presence of Blockagesen_US
dc.typeArticleen_US

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