Latency and power optimization in terahertz UAV-assisted vehicular networks across diverse atmospheric profile conditions

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dc.contributor.authorKorpe, Enis
dc.contributor.authorAkkas, Mustafa Alper
dc.contributor.authorOzturk, Yavuz
dc.date.accessioned2026-01-24T12:30:59Z
dc.date.available2026-01-24T12:30:59Z
dc.date.issued2025
dc.departmentAlanya Alaaddin Keykubat Üniversitesi
dc.description.abstractTerahertz (THz) communication has emerged as a key technology for high-speed wireless networks, particularly in scenarios where conventional frequency bands fail to meet growing data demands. With its potential for ultra-low latency, broad bandwidth, and robust connectivity, THz communication offers a suitable infrastructure for intelligent transportation systems and autonomous vehicles, especially within Vehicle-to-Everything (V2X) and Unmanned Aerial Vehicle (UAV) communication networks. This study aims to optimize THz communication between UAVs and ground vehicles under varying atmospheric conditions. Specifically, an artificial intelligence (AI)-based scheme is proposed to simultaneously minimize latency and transmission power while maintaining a sufficient signal-to-noise ratio (SNR) for successful communication. The proposed method integrates a dual-objective Particle Swarm Optimization (PSO) algorithm with the Line-by-Line Radiative Transfer Model (LBLRTM), which accurately models atmospheric absorption characteristics. Designed for critical scenarios such as emergency response operations, the scheme dynamically determines UAV positions and transmission powers to ensure both energy efficiency and low-latency communication. Simulation results demonstrate that the proposed approach achieves sufficient SNR levels and low latency across all atmospheric models. These findings highlight the potential of the AI-based approach to enhance energy efficiency and ensure sustainable connectivity in THz-enabled networks for time-sensitive applications.
dc.identifier.doi10.1007/s11235-025-01343-6
dc.identifier.issn1018-4864
dc.identifier.issn1572-9451
dc.identifier.issue3
dc.identifier.scopus2-s2.0-105014717676
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.1007/s11235-025-01343-6
dc.identifier.urihttps://hdl.handle.net/20.500.12868/5556
dc.identifier.volume88
dc.identifier.wosWOS:001563241100001
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofTelecommunication Systems
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260121
dc.subjectTerahertz communication
dc.subjectVehicular networks
dc.subjectUAV
dc.subjectArtificial intelligence
dc.subjectLBLRTM
dc.titleLatency and power optimization in terahertz UAV-assisted vehicular networks across diverse atmospheric profile conditions
dc.typeArticle

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