Characteristics of RSSI Kriging Interpolated Value in Neighborhood of Buildings
Ryo Miyamoto, Shusuke Narieda, Takeo Fujii, Hiroshi Naruse
Abstract
Ryo Miyamoto, Shusuke Narieda, Takeo Fujii, Hiroshi Naruse
Abstract
This study investigates the effect of buildings on the accuracy of Kriging interpolation result for estimating for the received signal strength indicator (RSSI) in the sub-GHz band. The RSSI values can be estimated using Kriging interpolation, which is an interpolation method and that depends on the distance and shadowing components. Traditionally, the accuracy of estimation by Kriging interpolation in the neighborhood of a building has never been verified. In this study, analyses of the accuracy of Kriging interpolation in the neighborhood of a building are provided by comparing the actual observed RSSI values with the values estimated by Kriging interpolation. This study verifies that the estimation accuracy can be improved by changing the area where the observations used for Kriging interpolation are obtained and by increasing the number of observations used for interpolation, even in the neighborhood of buildings. In addition, estimation accuracy can be improved by obtaining the observed value from the area near the interpolated location.
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This study investigates the effect of buildings on the accuracy of Kriging interpolation result for estimating for the received signal strength indicator (RSSI) in the sub-GHz band. The RSSI values can be estimated using Kriging interpolation, which is an interpolation method and that depends on the distance and shadowing components. Traditionally, the accuracy of estimation by Kriging interpolation in the neighborhood of a building has never been verified. In this study, analyses of the accuracy of Kriging interpolation in the neighborhood of a building are provided by comparing the actual observed RSSI values with the values estimated by Kriging interpolation. This study verifies that the estimation accuracy can be improved by changing the area where the observations used for Kriging interpolation are obtained and by increasing the number of observations used for interpolation, even in the neighborhood of buildings. In addition, estimation accuracy can be improved by obtaining the observed value from the area near the interpolated location.
Key concepts: Kriging, Interpolation (computer graphics), Multivariate interpolation, Computer science, Mathematics, Nearest-neighbor interpolation, Statistics, Algorithm