Measurement-based study on the influence of localization errors on estimated shadow correlations

Nikos Perpinias, Alexandros Palaios, Janne Riihijärvi, P. Mähönen
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引用次数: 1

Abstract

In recent years, novel spectrum access schemes have increased the need to further explore and exploit radio propagation dynamics. One proposed approach is to use spectrum sensing nodes for propagation environment estimation, and particularly to allow shadowing field extraction. In general there is a tendency to develop techniques that allow the automated and localized estimation of the spatial correlation structure of the shadowing field. Key issue when using such data is to take into account inherent localization errors and the impact that it has on these estimates. In this paper we use real measurement data acquired with extremely high localization accuracy to demonstrate and study the impact of localization errors. We present results for the propagation estimation, the extracted shadow field, and estimated shadow correlations. In particular, we show that spatial correlation metrics such as semivariograms are robust against localization errors higher than arising from the typical embedded GPS chipsets, up to approximately 20 m. Moreover, we have considered various probability distributions of localization errors, exploring their impact into our analysis. The reported results are highly relevant to development of measurement-based coverage estimation techniques and planning of drive tests or understanding limits of crowd-sourced data from user devices.
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基于测量的定位误差对估计阴影相关影响的研究
近年来,新的频谱接入方案增加了进一步探索和利用无线电传播动力学的需求。一种被提出的方法是使用频谱感知节点进行传播环境估计,特别是允许阴影场提取。一般来说,有一种趋势是发展技术,允许自动和局部估计的空间相关结构的阴影场。使用这些数据时的关键问题是要考虑到固有的定位错误及其对这些估计的影响。本文采用具有极高定位精度的实测数据,对定位误差的影响进行了论证和研究。我们给出了传播估计、提取阴影场和估计阴影相关性的结果。特别是,我们表明,空间相关指标(如半变方差)对定位误差的鲁棒性高于典型嵌入式GPS芯片组产生的定位误差,误差可达约20米。此外,我们还考虑了定位误差的各种概率分布,探讨了它们对我们分析的影响。报告的结果与开发基于测量的覆盖估计技术和规划驾驶测试或了解来自用户设备的众包数据的限制高度相关。
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