智能超表面辅助的非正交多址接入车联网通感一体传输与资源分配优化  

RIS-Assisted ISAC with Non-orthogonal Multiple Access Transmission and Resource Allocation Optimization in Vehicular Networks

作　　者：李美玲[1] 朱芸灿 申陈宁 李兴旺 LI Meiling;ZHU Yuncan;SHEN Chenning;LI Xingwang(School of Electronics Information Engineering,Taiyuan University of Science and Technology,Taiyuan 030024,China;Shanxi Communication Tongda Microwave Technology Co.,Ltd.,Taiyuan 030006,China;School of Physics and Electronic Information Engineering,Henan Polytechnic University,Jiaozuo 454003,China)

机构地区：[1]太原科技大学电子信息工程学院,太原030024 [2]山西通信通达微波技术有限公司,太原030006 [3]河南理工大学物理与电子信息学院,焦作454000

出　　处：《电子与信息学报》2025年第4期1043-1051,共9页Journal of Electronics & Information Technology

基　　金：国家重点研发计划项目(2024YFE0200300);山西省科技创新人才团队专项计划(202304051001035);太原市双百攻关揭榜挂帅项目(2024TYJB0134);山西省科技成果转化引导专项(202204021301055);山西省留学人员科技活动择优资助项目(20240023);山西省科研实践创新类项目(2023KY647)。

摘　　要：为应对6G密集城市环境下车联网(V2X)通信和传感路径受限问题,该文提出了一种基于可重构智能超表面(RIS)辅助的通感一体化(ISAC)V2X系统框架。针对非视距(NLOS)下的车辆移动性,采用扩展卡尔曼滤波(EKF)算法,结合ISAC回波信号中的实时信道状态信息(CSI),实现对移动车辆位置的跟踪与预测。该文提出基于非正交多址接入技术(NOMA)的多车辆间功率分配优化方案,在保证感知精度的同时提升下行链路通信总速率,并引入Karush-Kuhn-Tucker(KKT)条件作为反馈机制,避免陷入局部最优。仿真结果表明,所提系统在通信性能和感知性能方面优于传统的RIS辅助ISAC-V2X系统。Objective To address the issue of limited V2X communication and sensing paths in 6G dense urban environments,an RIS-assisted ISAC-V2X system framework is proposed.Considering vehicle mobility under Non-Line-of-Sight(NLOS)conditions,the Extended Kalman Filter(EKF)algorithm is utilized to track and predict the positions of moving vehicles by combining real-time Channel State Information(CSI)from the ISAC echo signals.A multi-vehicle power allocation optimization scheme based on Non-Orthogonal Multiple Access(NOMA)is introduced to enhance the downlink communication sum rate while maintaining sensing accuracy.The Karush-Kuhn-Tucker(KKT)conditions are incorporated as a feedback mechanism to prevent the system from converging to a local optimum.Simulation results demonstrate that the proposed system outperforms the traditional RIS-assisted ISAC-V2X system in terms of both communication and sensing performance.Methods This study establishes an RIS-assisted ISAC-V2X-NOMA system model.Considering vehicle mobility in NLOS conditions,the EKF algorithm is employed to track and predict vehicle locations base on real-time CSI from the ISAC signals.Subsequently,a multi-vehicle power allocation optimization scheme based on NOMA is proposed,with the KKT conditions introduced to avoid local optima and ensure global optimality.To comprehensively evaluate channel estimation performance,1000 Monte Carlo simulations are conducted,and performance analyses are carried out on MATLAB with comparisons to traditional RIS-assisted ISAC-V2X systems under different scenarios,ultimately validating the superiority of the proposed system.Results and Discussions The sensor tracking performance of the proposed system is presented,which indicate that the introduction of RIS significantly improves the angle and distance tracking accuracy.As the number of RIS reflection elements increases,the system’s Root Mean Square Error(RMSE)decreases,validating the effectiveness of RIS in complex dynamic environments.Then,the communication performance analysis

关 键 词：车联网 通信感知一体化 可重构智能超表面 扩展卡尔曼滤波 非正交多址接入技术 

分 类 号：TN929.5[电子电信—通信与信息系统]