Improving V2I Communication Technology Based on Interference Analysis for Wireless Networks

Abstract

Intelligent transportation systems use three kinds of interactive cooperative communication to manage the urban road traffic. These are human to human communication (H2H), machine to human communication (M2H) and machine to machine communication (M2M). H2H communication is based mostly on human gestures involving the hands, face, eyes or other body parts. M2M communication is a hybrid system that is installed in autonomous vehicles (AVs) and responds to human gestures. It is found in three forms: vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-everything (V2X). In this paper, V2I communication will be studied to improve the internet communication of autonomous vehicles in 5G environment. V2I communication used to manage the platooning of vehicles on urban roads, which is a strategy for increasing road capacity. The performance of V2I communication is measured in terms of QoS parameters such as delay and interference. The interference analysis of wireless communications becomes increasingly difficult as the environment becomes increasingly complex This paper proposes an analytical model that integrate pathloss and cochannel interference, which are considered the most important factors contributing to the performance degradation of V2I communication. A discussion of the challenges of V2I communication and their impact on urban road management is presented. Improvements in V2I communication are intended to overcome the shortcomings of human divers by improving traffic flow, reducing accidents, and reducing social exclusion.