Adaptive Optimization and Performance Analysis of Resource Reservation in C-V2X

Cellular Vehicle-to-Everything (C-V2X) technology improves road traffic safety and efficiency by periodically broadcasting beacon messages. However, in high-density traffic environments, increased competition for channel resources significantly impacts communication performance. This paper proposes a set of optimization solutions for the Semi-Persistent Scheduling (SPS) algorithm. Firstly, using a mathematical analysis model, the factors influencing the probabilities of resource selection conflict, access conflict, and delay interruption are quantitatively assessed. Secondly, to address the static configuration limitations of the SPS algorithm in terms of perception range, transmission power, and resource reservation probability, three improvement strategies are proposed: adaptive perception range adjustment, adaptive power control, and resource reservation probability optimization, aimed at enhancing the system’s adaptability and stability in dynamic environments. Simulation results indicate that the proposed optimization mechanisms can significantly reduce access conflict probabilities and delay interruption probabilities under varying traffic densities, enhancing system resource utilization and communication reliability. It provides new theoretical support and practical guidance for resource management and protocol design of C-V2X network.