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Signal power distribution in time delay in Tokyo City experimental sites

机译:东京市实验场的时间延迟中的信号功率分布

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This paper presents experiments carried out in the city of Tokyo in two types of built-up environments. One environment is characterized by a straight-crossing street plan with buildings randomly lining the streets and the terminal antennas located at the line of sight (LOS) and quasi-LOS conditions along the streets. The second built-up area is characterized by straight-crossing streets with non-LOS (NLOS) conditions caused by the railway station and administrative buildings surrounding the terminal antennas. The time delay signal strength distributions obtained experimentally are presented for both multipath urban channels These test experiments are used to study whether any propagation modeling can predict the time delay distribution of signal power. Our theoretical framework is based on the corresponding crossing-street waveguide model taking into account the Poisson statistics for buildings randomly lining each street. The proposed analytical formulas are analyzed for different parameters of the built-up terrain, such as the street width, the average height of buildings, the terminal antenna heights with respect to the rooftops of buildings lining a street, and the gaps (slits) between the buildings. Then a comparison between the proposed theoretical model and experimental data is presented, which indicates a satisfactory agreement between the theoretical and experimental prediction of signal power distribution in the time delay domain. So, our modeling can be used as a promising predictor for the time delay distribution in the microcellular propagation environment.
机译:本文介绍了在东京市两种类型的建筑环境中进行的实验。一种环境的特点是街道规划是直交的,建筑物随机排列在街道上,终端天线位于视线(LOS)和沿街道的准LOS条件下。第二个建成区的特征是火车站和围绕终端天线的行政大楼造成的非LOS(NLOS)条件的直交街道。展示了通过实验获得的两个多径城市通道的时延信号强度分布。这些测试实验用于研究任何传播模型是否可以预测信号功率的时延分布。我们的理论框架基于相应的过街波导模型,其中考虑了随机排列在每条街道上的建筑物的泊松统计量。针对建筑地形的不同参数,分析了建议的分析公式,例如街道宽度,建筑物的平均高度,相对于建筑物沿街道的屋顶的终端天线高度以及之间的缝隙(狭缝)那些建筑。然后对所提出的理论模型和实验数据进行了比较,表明在时延域中信号功率分布的理论和实验预测之间令人满意的一致性。因此,我们的模型可以用作微细胞传播环境中时间延迟分布的有前途的预测指标。

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