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Stochastic geometry based models for modeling cellular networks in urban areas

机译:基于随机几何的城市区域蜂窝网络建模模型

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Recently a new approach to modeling cellular networks has been proposed based on the Poisson point process (PPP). Unlike the traditional, popular hexagonal grid model for the locations of base stations, the PPP model is tractable. It has been shown by Andrews et al. (in IEEE Trans Commun 59(11):3122-3134, 2011) that the hexagonal grid model provides upper bounds of the coverage probability while the PPP model gives lower bounds. In this paper, we perform a comprehensive comparison of the PPP and the hexagonal grid models with real base station deployments in urban areas worldwide provided by the open source project OpenCelllD. Our simulations show that the PPP model gives upper bounds of the coverage probabilities for urban areas and is more accurate than the hexagonal grid model. In addition, we show that the Poisson cluster process is able to accurately model the base station location distribution.
机译:最近,已经提出了一种基于泊松点过程(PPP)的蜂窝网络建模的新方法。与传统的,流行的基站位置六边形网格模型不同,PPP模型易于处理。安德鲁斯等人已经证明了这一点。 (在IEEE Trans Commun 59(11):3122-3134,2011中),六边形网格模型提供了覆盖概率的上限,而PPP模型给出了下限。在本文中,我们对由开源项目OpenCellID提供的PPP和六角形网格模型与真实市区中的实际基站部署进行了全面比较。我们的仿真表明,PPP模型给出了城市区域覆盖率的上限,并且比六边形网格模型更准确。此外,我们证明了泊松聚类过程能够准确地模拟基站位置分布。

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