福建电脑2025，Vol.41Issue(7)：1-6,6.DOI:10.16707/j.cnki.fjpc.2025.07.001
IRS辅助认知车联网抗干扰资源分配方法
Anti-Jamming Resource Allocation in IRS-Assisted Cognitive Internet of Vehicles
吴烽1
作者信息
- 1. 福州大学电气工程与自动化学院 福州 350108
- 折叠
摘要
Abstract
Cognitive connected vehicles are widely used to overcome the scarcity of spectrum resources,but malicious interference attacks pose a serious threat.To overcome this challenge,this article utilizes an intelligent reflective surface IRS to enhance communication performance.By jointly optimizing the resource allocation and IRS phase shift of vehicle users,the total transmission rate of V2I in the vehicle infrastructure link can be maximized.A heterogeneous multi-agent dual competitive deep Q-network algorithm combined with Transformer was proposed.The numerical results indicate that the algorithm can effectively improve the transmission rate of V2I links under different interference attacks.关键词
智能反射面/干扰攻击/深度强化学习/认知车联网/资源分配Key words
IRS/Anti-Jamming/Deep Reinforcement Learning/CIoV分类
信息技术与安全科学引用本文复制引用
吴烽..IRS辅助认知车联网抗干扰资源分配方法[J].福建电脑,2025,41(7):1-6,6.
