This paper explores the fundamental issue to conflicting performance requirements in 5G New Radio (5G NR) vehicle‐to‐everything (V2X) communications for autonomous driving applications. Unlike the previous literature where most of its studies consider single performance measures in a fixed or simplified environment, the proposed system presents a dynamic mathematical model that simultaneously represents the energy consumption, communication reliability, in the form of a packet delivery ratio, and end‐to‐end latency in dynamic and time‐varying vehicular conditions. The model has been proven, and the validity of its implementation is reflected in large‐scale simulations carried out in Python, with a dataset of more than 500,000 data points and a wide variety of traffic and mobility conditions. The findings make it evident that there is a strong inverse correlation that exists between vehicular density and the general level of communication quality, so that high traffic density results in a localized rise of the transmission delay and a grave decrease in the packet delivery performance. In addition, the analysis determines that there is a roughly linear trade‐off between energy conservation and minimizing latency that indicates the tension that exists between these two ends. All these results emphasize the exceptional necessity of adaptive and context‐aware resource management solutions in 5G NR V2X systems and can serve as a good quantitative benchmark to the design of further intelligent optimization and control algorithms.
Hamid et al. (Thu,) studied this question.