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Performance Optimization of WiFi–LiFi Heterogeneous Networks for Autonomous Vehicle Platooning

Bakhtiyor MakhkamovTashkent University of Information Technologies, Named After Muhammad al-Khwarizmi,Tashkent,UzbekistanIbrohimbek YusupovTashkent University of Information Technologies, Named After Muhammad al-Khwarizmi,Tashkent,UzbekistanDjamshid SultanovTashkent University of Information Technologies, Named After Muhammad al-Khwarizmi,Tashkent,UzbekistanMandeep SinghSt Soldier Group of Institutions,Department of Computer Science and Engineering,Jalandhar,IndiaJaspreet KaurLovely Professional University,School of Computer Science and Engineering,Phagwara,Punjab,IndiaGurpreet KaurLovely Professional University,School of Computer Science and Engineering,Phagwara,Punjab,India
2025
ABI

Annotatsiya

CAV platooning requires low-latency and reliable communication in order to coordinate vehicle motion, quick control responses, and consistent inter-vehicle distance. WiFi offers strong non-style of sight coverage but suffers in congestion and fluctuating lag in a busy traffic whereas LiFi offers full bandwidth, interference free links under both line-of-sight and dense traffic situations but is vulnerable to mobility and obstruction. The present paper includes a performance optimization framework of heterogeneous WiFiLiFi networks, specifically in autonomous platoons. A resource distribution and handover approach of mobility-awareness makes use of dynamic process of selecting the most appropriate communication interface according to forecasted link quality, vehicle geometry and latency needs. The model separates the mission-critical control traffic and highbandwidth sensor traffic. Comparison of the simulation results of WiFi-only, LiFi-only and hybrid deployments reveal that the proposed heterogeneous deployment method is significantly minimizing the control latency and enhancing the throughput. These results indicate that integrated WiFiLiFi systems are effective at satisfying very high communication requirements of autonomous vehicle platooning of the next generation.

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