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Performance analysis for heterogeneous cellular networks based on Matern-like point process model

机译:基于类Matern点过程模型的异构蜂窝网络性能分析

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Cellular networks have a great transformation during the last decade. The traditional cellular network system is often overlaid with well-deployed BSs of proper power. However, more and more complex elements such as picocells, femtocells and relays have been introduced to cellular network system. BSs in these elements are unplanned, user-installed and randomly deployed. All of these things compose heterogeneous cellular networks (HCNs). In order to evaluate the performance of HCNs, people usually model the distribution of BSs in HCNs as spatial stochastic point process model. One of the most popular spatial models for these HCNs is Poisson Point Process (PPP) model. However the PPP model is not exact for some cases where BSs in PPP model may be too close to each other. In this paper, we propose a more reasonable and practical model called Matern-like point process (MLPP) model which imposes a certain minimal distance between any two BSs to overcome this problem. Simulations show that the coverage probability of the proposed model noticeably outperforms the PPP model. This improvement depends on the value of minimal distance. We also evaluate the system efficiency defined by the ratio of coverage probability and total power. The results show that the MLPP model has a significant improvement compared to PPP model.
机译:在过去的十年中,蜂窝网络发生了巨大的变化。传统的蜂窝网络系统通常覆盖有部署适当功率的BS。然而,诸如微微小区,毫微微小区和中继之类的越来越复杂的元件已经被引入蜂窝网络系统。这些元素中的BS是未经计划的,用户安装的和随机部署的。所有这些构成了异构蜂窝网络(HCN)。为了评估HCN的性能,人们通常将HCN中BS的分布建模为空间随机点过程模型。这些HCN最受欢迎的空间模型之一是泊松点过程(PPP)模型。然而,在某些情况下,PPP模型并不精确,在某些情况下,PPP模型中的BS可能彼此过于靠近。在本文中,我们提出了一种更合理,更实用的模型,称为“类人点过程”(MLPP)模型,该模型在任意两个BS之间强加了一定的最小距离来克服此问题。仿真表明,该模型的覆盖概率明显优于PPP模型。这种改进取决于最小距离的值。我们还评估了由覆盖概率与总功率之比定义的系统效率。结果表明,与PPP模型相比,MLPP模型具有显着改进。

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