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Multi-Hop Connectivity Probability in Infrastructure-Based Vehicular Networks

机译:基于基础架构的车载网络中的多跳连接概率

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Infrastructure-based vehicular networks (consisting of a group of Base Stations (BSs) along the road) will be widely deployed to support Wireless Access in Vehicular Environment (WAVE) and a series of safety and non-safety related applications and services for vehicles on the road. As an important measure of user satisfaction level, uplink connectivity probability is defined as the probability that messages from vehicles can be received by the infrastructure (i.e., BSs) through multi-hop paths. While on the system side, downlink connectivity probability is defined as the probability that messages can be broadcasted from BSs to all vehicles through multi-hop paths, which indicates service coverage performance of a vehicular network. This paper proposes an analytical model to predict both uplink and downlink connectivity probabilities. Our analytical results, validated by simulations and experiments, reveal the trade-off between these two key performance metrics and the important system parameters, such as BS and vehicle densities, radio coverage (or transmission power), and maximum number of hops. This insightful knowledge enables vehicular network engineers and operators to effectively achieve high user satisfaction and good service coverage, with necessary deployment of BSs along the road according to traffic density, user requirements and service types.
机译:基于基础设施的车辆网络(由沿途的一组基站(BS)组成)将被广泛部署,以支持车辆环境中的无线访问(WAVE)以及一系列针对车辆的安全性和非安全性相关的应用程序和服务马路。作为用户满意度的重要度量,上行链路连接概率定义为基础设施(即BS)可以通过多跳路径从车辆接收消息的概率。在系统方面,下行链路连通性概率定义为消息可以通过多跳路径从BS广播到所有车辆的概率,这表明了车辆网络的服务覆盖范围。本文提出了一种分析模型来预测上行链路和下行链路的连接概率。我们的分析结果通过仿真和实验验证,揭示了这两个关键性能指标与重要系统参数(例如,BS和车辆密度,无线电覆盖范围(或发射功率)以及最大跳数)之间的折衷。这种洞察力丰富的知识使车辆网络工程师和运营商能够根据流量密度,用户要求和服务类型在道路上进行必要的BS部署,从而有效地实现较高的用户满意度和良好的服务覆盖范围。

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