AI-Driven Optimization of THz Vehicular Communication
Bildiriler > Tam Metin Bildiri
Yazarlar: Enis Körpe, Mustafa Alper Akkaş, Yavuz ÖZTÜRK
2025 33rd Telecommunications Forum (TELFOR), , , Uluslararası, Tam Metin Bildiri, ss 1-4
DOI: 10.1109/telfor67910.2025.11314237
Özet
Terahertz (THz) communication (0.1-10 THz) offers ultra-high data rates for future vehicular networks, addressing growing data demands and low-latency requirements. This study models a single-lane THz vehicular scenario, comparing a random topology with AI-driven optimization using Particle Swarm Optimization (PSO) and the Firefly Algorithm (FA) in terms of energy efficiency and the total path loss. Using High-Resolution Transmission Molecular Absorption Database (HITRAN) for atmospheric absorption modeling, results show that AI methods significantly reduce the total path loss and minimum required transmit power, with PSO outperforming FA in computational efficiency. These findings highlight the promise of AI-assisted optimization in enhancing THz vehicular communication.