Ray-Tracing 5G Channels from Scenarios with Mobility Control of Vehicles and Pedestrians
Ray-Tracing 5G Channels from Scenarios with Mobility Control of Vehicles and Pedestrians
复制标题
车辆和行人移动控制场景中的光线追踪 5G 通道
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
A. Klautau
中科院分区：
文献类型：
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作者：
A. Oliveira;Marcus Dias;Isabela Trindade;A. Klautau
毫米波是实现高比特率的5G网络策略之一。使用这些信号进行测量是困难的，并且需要昂贵的设备。为了生成逼真的数据，本文改进了一种5G通道虚拟测量的方法，将城市流动性模拟与光线跟踪模拟器相结合。城市流动性模拟器负责控制流动性，在每个场景中定位行人和车辆，同时重复调用光线跟踪模拟器，模拟接收器和发射器之间的相互作用。两个模拟器之间的协调是使用Python软件完成的。为了检验真实感对计算代价的影响，对面数和模拟时间进行了数值分析。
Millimeter waves is one of 5G networks strategies to achieve high bit rates. Measurement campaigns with these signals are difficult and require expensive equipment. In order to generate realistic data this paper refines a methodology for virtual measurements of 5G channels, which combines a simulation of urban mobility with a ray-tracing simulator. The urban mobility simulator is responsible for controlling mobility, positioning pedestrians and vehicles throughout each scene while the ray-tracing simulator is repeatedly invoked, simulating the interactions between receivers and transmitters. The orchestration among both simulators is done using a Python software. To check how the realism can influence the computational cost, it was made a numerical analyze between the number of faces and the simulation time.