面向信息新鲜度保障的车联网功率控制和资源分配策略  

Power Control and Resource Allocation Strategy for Information Freshness Guarantee in Internet of Vehicles

作　　者：杨鹏[1,2,3] 康一铭 杨静 唐桐[1] 祝志远 吴大鹏 YANG Peng;KANG Yiming;YANG Jing;TANG Tong;ZHU Zhiyuan;WU Dapeng(School of Communications and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China;China Academy of Information and Communications Technology,Beijing 100191,China;Institute of Information and Communications Technology Innovation Co.,Ltd.,Xi’an 710116,China)

机构地区：[1]重庆邮电大学通信与信息工程学院,重庆400065 [2]中国信息通信研究院,北京100191 [3]信通院(西安)科技创新有限公司,西安710116

出　　处：《电子与信息学报》2025年第2期498-509,共12页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(U24A20211,62271096,U20A20157);重庆市自然科学基金(CSTB2023NSCQ-LZX0134,CSTB2024NSCQLZX0124);重庆市高校创新研究群体项目(CXQT20017);重邮信通青创团队支持计划(SCIE-QN-2022-04)。

摘　　要：在差异化服务共存的车联网场景中,针对基于平均信息年龄(AoI)优化无法降低极端事件发生概率的问题,该文提出一种信息新鲜度保障的用户功率控制和资源分配策略。首先,根据系统模型刻画出车辆到车辆(V2V)用户状态更新信息新鲜度约束下最大化车辆到基站(V2I)用户体验质量(QoE)的问题。然后,结合与AoI中断约束等价的队列积压约束,并引入极值理论以优化AoI尾部分布。接着,基于李雅普诺夫优化方法将原问题转化最小化李雅普诺夫漂移加惩罚函数的问题,在此基础上求解最优的用户发射功率。最后,在构建超图的基础上,提出了一种基于遗传算法改进粒子群算法(GA-PSO)的资源分配策略确定最优的用户信道复用方式。仿真结果表明,相比于基准方案,所提方案能够在降低V2V链路AoI中断的极端事件发生概率的同时,提高约7.03%的V2I链路信道容量,实现V2I用户平均QoE提升。Objective In the Internet of Vehicles(IoV),where differentiated services coexist,the system is progressively evolving towards safety and collaborative control applications,such as autonomous driving.Current research primarily focuses on optimizing mechanisms for high reliability and low latency,with Quality of Service(QoS)parameters commonly used as benchmarks,while the timeliness of vehicle status updates receives less attention.Merely optimizing metrics like transmission delay and throughput is insufficient for ensuring that vehicles obtain status information in a timely manner.For example,in security-critical IoV applications,which require the exchange of state information between vehicles,meeting only the constraints of delay interruption probability or data transmission interruption does not fully address the high timeliness requirements of security services.To tackle this challenge and meet the stringent timeliness demands of security and collaborative applications,this paper proposes a user power control and resource allocation strategy aimed at ensuring information freshness.Methods This paper investigates user power control and resource allocation strategies to ensure information freshness.First,the problem of maximizing the Quality of Experience(QoE)for Vehicle-to-Infrastructure(V2I)users under the constraint of freshness in Vehicle-to-Vehicle(V2V)status updates is formulated based on the system model.Then,by incorporating the queue backlog constraint,equivalent to the Age of Information(AoI)violation constraint,the extreme value theory is applied to optimize the tail distribution of AoI.Furthermore,using the Lyapunov optimization method,the original problem is transformed into minimizing the Lyapunov drift plus a penalty function,based on which the optimal user transmission power is determined.Finally,a resource allocation strategy based on Genetic Algorithm improved Particle Swarm Optimization(GA-PSO)is proposed,leveraging a hypergraph structure to determine the optimal user channel reuse mode.Results

关 键 词：资源分配 功率控制 信息年龄 极端事件 

分 类 号：TN929.5[电子电信—通信与信息系统]