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General N-State Markov Model for Rain Attenuation Time Series Generation

机译:降雨衰减时间序列生成的通用N状态马尔可夫模型

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摘要

Nowadays and mainly in the near future the wireless point-to-point or point-to-multipoint connections are operating in high frequency. These systems are applied in feeder network for future cellular mobile communication systems or BFWA (Broadband Fixed Wireless Access) networks. Besides the obvious benefits of the applied high carrier frequency there is a significant disadvantage, the considerable attenuation caused by precipitation, especially by rain. For accurate planning of the proposed microwave links the statistics of the expectable rain attenuation is highly important. Applying our previous research results the this work provides a general N-state Markov Chain model to generate rain attenuation time series on a proposed microwave link according to the link parameters. The first and second order rain attenuation statistics of the generated time series can be derived directly from the Markov model parameters, so the N-state Markov model can be applied for prediction of rain attenuation on the proposed link even in the early planning phase. With our proposed model very accurate realisation of the physical fade process can be achieved.
机译:如今且主要是在不久的将来,无线点对点或点对多点连接将以高频率运行。这些系统应用于未来的蜂窝移动通信系统或BFWA(宽带固定无线接入)网络的馈线网络中。除了应用高载波频率带来的明显好处外,还有一个明显的缺点,即由于降水(尤其是雨水)而引起的相当大的衰减。为了精确规划所提议的微波链路,预期雨衰的统计非常重要。应用我们以前的研究结果,这项工作提供了一个通用的N状态马尔可夫链模型,可以根据链路参数在拟议的微波链路上产生降雨衰减时间序列。可以直接从马尔可夫模型参数中得出生成的时间序列的一阶和二阶降雨衰减统计量,因此即使在早期规划阶段,也可以将N状态马尔可夫模型用于所提议的链路上的降雨衰减预测。使用我们提出的模型,可以非常精确地实现物理淡入淡出过程。

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