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Worst Month Tropospheric Attenuation Variability Analysis: ITU Model vs. Rain Gauge Data for Air-Satellite Links

机译:最糟糕的月份对象衰减可变性分析:ITU模型与雨量雨量空气卫星链路数据

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An important unmanned aircraft system (UAS) application area is in rescue functions in remote areas, where ground station control may not be applicable. In such settings, an air-satellite (AS) communication link may be required. For transmissions in the millimeter wave (mmWave) frequency bands, rain attenuation can be a dominant fading component in the AS link, especially in so-called “worst month” conditions. Several models have been established by the International Telecommunications Union (ITV) to quantify rain attenuation. However, since the models are for global use, results are not always sufficiently accurate in local areas. Hence the use of local precipitation data can improve rain attenuation estimation accuracy. In this paper, we investigate attenuations in the AS channel in two frequency bands (30 and 45 GHz) for Columbia, SC. We use local rain gauge data from the National Oceanic and Atmospheric Administration (NOAA), along with the regional ITV data, as inputs to the ITV tropospheric time series attenuation model. Statistical results for attenuation distributions and time series are analyzed for the worst month. We show that use of local measured rain gauge data can yield rain fades significantly larger than those predicted by the regional ITV data-on the order of 20 dB larger, for probabilities (~ fractions of time) ranging from 0.001 to 0.04.
机译:一个重要的无人驾驶飞机系统(UAS)应用领域是遥控领域的救援功能,地面控制可能不适用。在这种设置中,可能需要空气卫星(AS)通信链路。对于毫米波(MMWAVE)频带中的传输,雨衰减可以是作为链路的主要衰落组件,尤其是所谓的“最糟糕的月份”条件。国际电信联盟(ITV)建立了几种模型,以量化雨衰减。但是,由于模型用于全球使用,因此当地区域并不总是充分准确。因此,局部降水数据的使用可以提高雨衰减估计精度。在本文中,我们研究了哥伦比亚SC的两个频段(30和45 GHz)中AS频段的衰减。我们使用来自国家海洋和大气管理(NOAA)的本地雨量数据,以及区域ITV数据,作为ITV对​​流层时间序列衰减模型的输入。分析了衰减分布和时间序列的统计结果,以进行最糟糕的一个月。我们表明,使用局部测量的雨量数据数据可以促使雨水衰落明显大于由区域ITV数据预测的那些,大约20dB更大,概率(〜级)从0.001〜0.04的概率范围内。

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