论文标题
联合通信感应车辆网络中合作检测的性能：数据分析和随机几何方法
Performance of Cooperative Detection in Joint Communication-Sensing Vehicular Network: A Data Analytic and Stochastic Geometry Approach
论文作者
论文摘要
城市环境的复杂性日益增加为自动驾驶汽车网络的部署带来了额外的不确定性。本文提出了一种新型的使用联合通信和传感（JCS）技术的新型道路基础设施合作检测模型，以同时实现高效的通信和城市自动驾驶汽车的障碍检测。为了抑制由JCS信号阴影和阻塞引起的性能波动，我们首先得出了地理信息系统（GIS）的道路障碍统计数据。然后，在复杂的城市场景下，使用视线和非视线（LOS和NLOS）通道模型对JCS通道特征和阴影因子进行分析。采用随机几何方法来分析成功JCS检测和通信的干扰因素和概率分布。已经进行了仿真来通过基于LOS和NLOS通道的概率分析来验证合作检测模型，并且数值结果证明了用于部署JCS Road基础架构的几种不同优化方法。最后，我们为JCS Road基础设施进行了模拟和分析，该方法符合城市交通点结构位置的标准。
The increasing complexity of urban environments introduces additional uncertainty to the deployment of the autonomous vehicular network. A novel road infrastructure cooperative detection model using Joint Communication and Sensing (JCS) technology is proposed in this article to simultaneously achieve high-efficient communication and obstacle detection for urban autonomous vehicles. To suppress the performance fluctuation caused by shadowing and obstruction to the JCS signals, we first derive the statistic of road obstacles from the Geographic Information System (GIS). Then, the analysis of JCS channel characteristics and shadowing factors are presented using Line-of-Sight and Non-Line-of-Sight (LoS and NLoS) channel models under the complex urban scenario. A stochastic geometry approach is applied to analyze the interference factors and the probability distribution of successful JCS detection and communication. Simulations have been made to verify the cooperative detection model by probability analysis based on LoS and NLoS channels, and the numerical results demonstrate several different optimization methods for the deployment of JCS road infrastructures. Finally, we simulated and analyzed a deployment optimization method for JCS road infrastructures that complied with the standard of urban traffic-spot structure placement.
