Statistical distribution of position error in weighted centroid localization

K. Magowe, A. Giorgetti, K. Sithamparanathan, Xinghuo Yu
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引用次数: 6

Abstract

Weighted centroid localization (WCL) based on received signal strength (RSS) measurements is an attractive low-complexity solution that enables cognitive radios (CRs) to have a geolocation awareness of the radio environment. In this paper, we propose a new analytical framework to accurately calculate the performance of WCL based on the statistical distribution of the ratio of two quadratic forms in normal variables. In particular, we derive an exact expression for the cumulative distribution function (CDF) of the two-dimensional location estimation in the presence of independent and identically distributed (i.i.d.) as well as correlated shadowing. Numerical results confirm that the analytical framework is able to predict the performance of WCL capturing all the essential aspects of propagation as well as CR network spatial topology.
加权质心定位中位置误差的统计分布
基于接收信号强度(RSS)测量的加权质心定位(WCL)是一种有吸引力的低复杂性解决方案,它使认知无线电(cr)能够对无线电环境进行地理位置感知。本文提出了一种新的分析框架,基于正态变量中两个二次型比率的统计分布来精确计算WCL的性能。特别地,我们导出了在独立和同分布(i.i.d)和相关阴影存在下二维位置估计的累积分布函数(CDF)的精确表达式。数值结果证实,该分析框架能够预测WCL的性能,捕获传播的所有基本方面以及CR网络的空间拓扑结构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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