基于车辆位置和相关性的协作频谱感知算法  

Cooperative Spectrum Sensing Algorithm Based on Vehicle Location and Correlation

作　　者：齐嘉杰 胡斌杰[1] QI Jiajie;HU Binjie(South China University of Technology,Guangzhou 510640,China)

机构地区：[1]华南理工大学

出　　处：《移动通信》2019年第11期14-20,共7页Mobile Communications

基　　金：国家自然科学基金(61871193);广东省自然科学基金重点项目(2018B030311049)

摘　　要：考虑路径损耗和阴影效应对认知车辆接收信号的影响,提出了一种基于车辆位置和相关性的协作感知算法。所提算法在保证感知性能的同时,尽可能选取较少的感知节点参与协作,接着提出一种介于硬判决融合和软判决融合之间的数据融合方法,参与协作的认知车辆上传2 bit的本地感知信息到路侧单元进行线性加权融合判决。仿真结果表明,所提算法与现有频谱感知算法相比有了很好的改进,取得了感知性能和感知开销的折中。Considering the influence of path loss and shadow effect on the received signal of cognitive vehicles,this paper proposes a cooperative sensing algorithm based on vehicle position and correlation.While guaranteeing the sensing performance,the proposed algorithm selects fewer sensing nodes to participate in the cooperative sensing.Then,a data fusion method between hard decision fusion and soft decision fusion is proposed.Cognitive vehicles participating in the cooperative sensing upload 2bit local sensing information to the RSUs for linear weighted fusion decision.The simulation results show that the proposed algorithm outperforms the existing spectrum sensing algorithms,and achieves the tradeo ff between sensing performance and sensing overhead.

关 键 词：认知车联网 频谱感知 协作节点 数据融合 

分 类 号：TN929.5[电子电信—通信与信息系统]