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Modeling Heterogeneous Cellular Networks Interference Using Poisson Cluster Processes

机译:使用泊松聚类过程建模异构蜂窝网络干扰

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摘要

Future mobile networks are converging toward heterogeneous multitier networks, where macro-, pico-, and femto-cells are randomly deployed based on user demand. A popular approach for analyzing heterogeneous networks (HetNets) is to use stochastic geometry and treat the location of BSs as points distributed according to a homogeneous Poisson point process (PPP). However, a PPP model does not provide an accurate model for the interference when nodes are clustered around highly populated areas. This motivates us to find better ways to characterize the aggregate interference when transmitting nodes are clustered following a Poisson cluster process (PCP) while taking into consideration the fact that BSs belonging to different tiers may differ in terms of transmit power, node densities, and link reliabilities. To this end, we consider -tier HetNets and investigate the outage probability, the coverage probability, and the average achievable rate for such networks. We compare the performance of HetNets when nodes are clustered and otherwise. By comparing these two types of networks, we conclude that the fundamental difference between a PPP and a PCP is that, for a PPP, the number of simultaneously covered mobiles and the network capacity linearly increase with . However, for a PCP, the improvements in the coverage and the capacity diminish as grows larger, where the curves saturate at some point. Based on these observations, we determine the scenarios that jointly maximize the average achievable rate and minimize the outage probability.
机译:未来的移动网络正在向异构多层网络汇聚,在该网络中,将根据用户需求随机部署宏小区,微微小区和毫微微小区。分析异构网络(HetNets)的一种流行方法是使用随机几何结构,并将BS的位置视为根据齐次Poisson点过程(PPP)分布的点。但是,当节点聚集在人口稠密的地区周围时,PPP模型无法为干扰提供准确的模型。这促使我们寻找更好的方法来表征在遵循Poisson群集过程(PCP)进行群集的发送节点群集时的总干扰,同时要考虑到属于不同层的BS在发送功率,节点密度和链路方面可能会有所不同的事实可靠性。为此,我们考虑使用分层的HetNet,并研究此类网络的中断概率,覆盖概率和平均可达到的速率。我们比较了群集节点和其他节点时HetNets的性能。通过比较这两种类型的网络,我们得出结论,PPP和PCP之间的根本区别在于,对于PPP,同时覆盖的移动台数量和网络容量随线性增加。但是,对于PCP,覆盖范围和容量的提高会随着曲线的增大而逐渐减小,而曲线在某个点会饱和。基于这些观察结果,我们确定了共同使平均可实现率最大化并使中断概率最小化的方案。

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