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首页> 外文期刊>IEEE transactions on wireless communications >Modeling and Performance Analysis of Clustered Device-to-Device Networks
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Modeling and Performance Analysis of Clustered Device-to-Device Networks

机译:群集设备到设备网络的建模和性能分析

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Device-to-device (D2D) communication enables direct communication between proximate devices thereby improving the overall spectrum utilization and offloading traffic from cellular networks. This paper develops a new spatial model for D2D networks in which the device locations are modeled as a Poisson cluster process. Using this model, we study the performance of a typical D2D receiver in terms of coverage probability under two realistic content availability setups: 1) content of interest for a typical device is available at a device chosen uniformly at random from the same cluster, which we term uniform content availability, and 2) content of interest is available at the closest device from the typical device inside the same cluster, which we term -closest content availability. Using these coverage probability results, we also characterize the area spectral efficiency (ASE) of the whole network for the two setups. A key intermediate step in this analysis is the derivation of the distributions of distances from a typical device to both the intra- and inter-cluster devices. Our analysis reveals that an optimum number of D2D transmitters must be simultaneously activated per cluster in order to maximize ASE. This can be interpreted as the classical tradeoff between more aggressive frequency reuse and higher interference power. The optimum number of simultaneously transmitting devices and the resulting ASE increase as the content is made available closer to the receivers. Our analysis also quantifies the best and worst case performance of clustered D2D networks both in terms of coverage and ASE.
机译:设备到设备(D2D)通信实现了附近设备之间的直接通信,从而提高了整体频谱利用率,并减轻了蜂窝网络的流量负担。本文为D2D网络开发了一种新的空间模型,其中将设备位置建模为Poisson集群过程。使用此模型,我们在两种现实的内容可用性设置下根据覆盖概率研究了典型D2D接收器的性能:1)典型设备的兴趣内容可从同一集群中随机选择的设备中获得,我们术语“统一内容可用性”,以及2)感兴趣的内容可从同一群集内的典型设备从最近的设备获得,我们称之为“最接近的内容可用性”。使用这些覆盖概率结果,我们还可以针对这两种设置来表征整个网络的区域频谱效率(ASE)。此分析中的关键中间步骤是推导从典型设备到群集内和群集间设备的距离分布。我们的分析表明,每个集群必须同时激活最佳数量的D2D发射机,才能使ASE最大化。这可以解释为更积极的频率重用和更高的干扰功率之间的经典权衡。随着内容变得更接近接收者,同时发送设备的最佳数量和所产生的ASE会增加。我们的分析还根据覆盖范围和ASE量化了集群D2D网络的最佳和最差情况性能。

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