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

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.