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Geometry-Based Vehicle-to-Vehicle Channel Modeling for Large-Scale Simulation

机译:大规模仿真的基于几何的车到车通道建模

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摘要

Due to the dynamic nature of vehicular traffic and the road surroundings, vehicle-to-vehicle (V2V) propagation characteristics vary greatly on both small and large scale. Recent measurements have shown that both large static objects (e.g., buildings and foliage) and mobile objects (surrounding vehicles) have a profound impact on V2V communication. At the same time, system-level vehicular ad hoc network (VANET) simulators by and large employ simple statistical propagation models, which do not account for surrounding objects explicitly. We designed Geometry-based Efficient propagationModel for V2V communication (GEMV2), which uses outlines of vehicles, buildings, and foliage todistinguish the following three types of links: line of sight (LOS), non-LOS (NLOS) due to vehicles, and NLOS due to static objects. For each link, GEMV2 calculates the large-scale signal variations deterministically, whereas the small-scale signal variations are calculated stochastically based on the number and size of surrounding objects. We implement GEMV2 in MATLAB and show that it scales well by using it to simulate radio propagation for city-wide networks with tens of thousands of vehicles on commodity hardware. We make the source code of GEMV2 freely available. Finally, we validate GEMV2 against extensive measurements performed in urban, suburban, highway, and open-space environments.
机译:由于车辆交通和道路周围环境的动态特性,车辆到车辆(V2V)的传播特性在小范围和大范围都存在很大差异。最近的测量表明,大型静态对象(例如建筑物和树叶)和移动对象(周围的车辆)都对V2V通信产生了深远的影响。同时,大体上系统级的车载自组织网络(VANET)仿真器采用简单的统计传播模型,这些模型没有明确考虑周围物体。我们设计了用于V2V通信(GEMV2)的基于几何的有效传播模型,该模型使用车辆,建筑物和树叶的轮廓来区分以下三种类型的链接:视线(LOS),非视距(NLOS)(由于车辆而引起的)以及由于静态对象而导致NLOS。对于每个链接,GEMV2确定性地计算大型信号变化,而小型信号变化是根据周围物体的数量和大小随机计算的。我们在MATLAB中实现了GEMV2,并证明了它的可扩展性,可以通过它模拟商用硬件上具有成千上万辆汽车的城市范围网络的无线电传播。我们免费提供GEMV2的源代码。最后,我们针对在城市,郊区,高速公路和开放空间环境中进行的广泛测量验证了GEMV2。

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