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3D Non-Stationary Wideband Tunnel Channel Models for 5G High-Speed Train Wireless Communications

机译:用于5G高速列车无线通信的3D非平稳宽带隧道通道模型

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High-speed train (HST) communications in tunnels have attracted more and more research interests recently, especially within the framework of the fifth generation (5G) wireless networks. In this paper, based on cuboid-shape, three-dimensional (3D) non-stationary wideband geometry-based stochastic models (GBSMs) for HST tunnel scenarios are proposed. By considering the influence of the tunnel walls, a theoretical channel model is first established, which assumes clusters with an infinite number of scatterers randomly distributed on the tunnel walls. The corresponding simulation model is then developed and the method of equal areas is employed to obtain the discrete parameters, such as the azimuth and elevation angles. We derive and investigate the most important channel statistical properties of the proposed 3D GBSMs, including the time-variant autocorrelation function, spatial cross-correlation function, and Doppler power spectrum density. It is indicated that all statistical properties of the simulation model, verified by simulation results, can match very well with those of the theoretical model. Furthermore, a validation is presented by comparing the stationary regions of our proposed tunnel channel model to those of relevant measurement data.
机译:隧道中的高速列车(HST)通信近来吸引了越来越多的研究兴趣,尤其是在第五代(5G)无线网络的框架内。在本文中,基于长方体形状,提出了用于HST隧道场景的基于三维(3D)非平稳宽带几何的随机模型(GBSM)。通过考虑隧道壁的影响,首先建立了理论通道模型,该模型假设了具有无限数量散射体的簇随机分布在隧道壁上。然后开发相应的仿真模型,并采用等面积方法获得离散参数,例如方位角和仰角。我们推导并研究了所提出的3D GBSM的最重要的信道统计特性,包括时变自相关函数,空间互相关函数和多普勒功率谱密度。结果表明,通过仿真结果验证的仿真模型的所有统计属性都可以与理论模型很好地匹配。此外,通过将我们提出的隧道通道模型的静止区域与相关测量数据的静止区域进行比较,提出了一种验证。

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