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Precise Asymptotic Distribution of the Number of Isolated Nodes in Wireless Networks with Lognormal Shadowing

机译:具有对数正态阴影的无线网络中孤立节点数的精确渐近分布

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In this paper, we study the connectivity of multihop wireless networks under the log-normal shadowing model by investigating the precise distribution of the number of isolated nodes. Under such a realistic shadowing model, all previous known works on the distribution of the number of isolated nodes were obtained only based on simulation studies or by ignoring the important boundary effect to avoid the challenging technical analysis, and thus cannot be applied to any practical wireless networks. It is extremely challenging to take the complicated boundary effect into consideration under such a realistic model because the transmission area of each node is an irregular region other than a circular area. Assume that the wireless nodes are represented by a Poisson point process with densitynover a unit-area disk, and that the transmission power is properly chosen so that the expected node degree of the network equals lnn + ξ (n), where ξ (n) approaches to a constant ξ as n →?∞. Under such a shadowing model with the boundary effect taken into consideration, we proved that the total number of isolated nodes is asymptotically Poisson with mean e$ {-ξ}. The Brun’s sieve is utilized to derive the precise asymptotic distribution. Our results can be used as design guidelines for any practical multihop wireless network where both the shadowing and boundary effects must be taken into consideration.
机译:在本文中,我们通过研究隔离节点数的精确分布,研究了对数正态阴影模型下的多跳无线网络的连通性。在这样一个现实的阴影模型下,关于隔离节点数量分布的所有先前已知工作仅基于仿真研究或通过忽略重要的边界效应而避免了具有挑战性的技术分析,因此无法应用于任何实际的无线网络。网络。在这种现实模型下考虑复杂的边界效应是极具挑战性的,因为每个节点的透射区域是除圆形区域以外的不规则区域。假设无线节点由单位面积磁盘上具有密度的泊松点过程表示,并且已正确选择传输功率,以使网络的预期节点度等于lnn +ξ(n),其中ξ(n)接近常数ξ为n→?∞。在考虑了边界效应的这种阴影模型下,我们证明了孤立节点的总数是渐近泊松的,均值为e $ {-ξ}。 Brun的筛子用于得出精确的渐近分布。我们的结果可以用作任何实际的多跳无线网络的设计指南,其中必须同时考虑阴影和边界效应。

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