Age of Information Analysis for Multi-Priority Queue and NOMA Enabled C-V2X in IoV
Zheng Zhang, Qiong Wu, Pingyi Fan, Ke Xiong
TL;DR
This work analyzes AoI as a unified measure of reliability and latency in C-V2X Mode 4 under SPS-driven resource contention. It proposes a mathematical framework with a four-queue multi-priority model and integrates NOMA with SIC to evaluate AoI in both queueing and transmission stages across varying RRIs. The study derives AoI evolution equations and SINR-based transmission success criteria, and demonstrates via MATLAB simulations that NOMA improves success rates and reduces AoI, particularly at higher vehicle densities, while the choice of $RRI$ critically balances collision probability and queuing delay. The findings offer a pathway to design more reliable, low-latency IoV communications with prioritized traffic and collision-mitigation techniques.
Abstract
As development Internet-of-Vehicles (IoV) technology and demand for Intelligent Transportation Systems (ITS) increase, there is a growing need for real-time data and communication by vehicle users. Traditional request-based methods face challenges such as latency and bandwidth limitations. Mode 4 in Connected Vehicle-to-Everything (C-V2X) addresses latency and overhead issues through autonomous resource selection. However, Semi-Persistent Scheduling (SPS) based on distributed sensing may lead to increased collision. Non-Orthogonal Multiple Access (NOMA) can alleviate the problem of reduced packet reception probability due to collisions. Moreover, the concept of Age of Information (AoI) is introduced as a comprehensive metric reflecting reliability and latency performance, analyzing the impact of NOMA on C-V2X communication system. AoI indicates the time a message spends in both local waiting and transmission processes. In C-V2X, waiting process can be extended to queuing process, influenced by packet generation rate and Resource Reservation Interval (RRI). The transmission process is mainly affected by transmission delay and success rate. In C-V2X, a smaller selection window (SW) limits the number of available resources for vehicles, resulting in higher collision rates with increased number of vehicles. SW is generally equal to RRI, which not only affects AoI in queuing process but also AoI in the transmission process. Therefore, this paper proposes an AoI estimation method based on multi-priority data type queues and considers the influence of NOMA on the AoI generated in both processes in C-V2X system under different RRI conditions. This work aims to gain a better performance of C-V2X system comparing with some known algorithms.