Asymptotic Blind-Spot Analysis of Localization Networks Under Correlated Blocking Using a Poisson Line Process

作者：Aditya Sundar^*; Dhillon Harpreet S; Molisch Andreas F; Behairy Hatim

来源：IEEE Wireless Communications Letters, 2017, 6(5): 654-657.

DOI：10.1109/LWC.2017.2727490

• Asymptotic blind-spot probability
• correlated blocking
• Poisson line process
• stochastic geometry
• Poisson-Voronoi tessellation

In a localization network, the line-of-sight between anchors (transceivers) and targets may be blocked due to the presence of obstacles in the environment. Due to the non-zero size of the obstacles, the blocking is typically correlated across both anchor and target locations, with the extent of correlation increasing with obstacle size. If a target does not have line-ofsight to a minimum number of anchors, then its position cannot be estimated unambiguously and is, therefore, said to be in a blind-spot. However, the analysis of the blind-spot probability of a given target is challenging due to the inherent randomness in the obstacle locations and sizes. In this letter, we develop a new framework to analyze the worst-case impact of correlated blocking on the blind-spot probability of a typical target; in particular, we model the obstacles by a Poisson line process and the anchor locations by a Poisson point process. For this setup, we define the notion of the asymptotic blind-spot probability of the typical target and derive a closed-form expression for it as a function of the area distribution of a typical Poisson-Voronoi cell. As an upper bound for the more realistic case when obstacles have finite dimensions, the asymptotic blind-spot probability is useful as a design tool to ensure that the blind-spot probability of a typical target does not exceed a desired threshold, is an element of.

• 出版日期2017-10
• 单位Virginia Tech; 美国弗吉尼亚理工大学(Virginia Tech)