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Nonparametric Model Comparison and Uncertainty Evaluation for Signal Strength Indoor Location.

dc.contributor.authorFiguera Pozuelo, Carlos
dc.contributor.authorMora Jimenez, I
dc.contributor.authorGuerrero Curieses, A
dc.contributor.authorRojo-Álvarez, José Luis
dc.contributor.authorEverss, E
dc.contributor.authorWilby, M
dc.contributor.authorRamos López, J
dc.description.abstractIndoor Location (IL) using Received Signal Strength (RSS) is receiving much attention, mainly due to its ease of use in deployed IEEE 802.11b (WiFi) wireless networks. Fingerprinting is the most widely used technique. It consists of estimating position by comparison of a set of RSS measurements, made by the mobile device, with a database of RSS measurements whose locations are known. However, the most convenient data structure to be used, and the actual performance of the proposed fingerprinting algorithms, are still controversial. In addition the statistical distribution of indoor RSS is not easy to characterize. Therefore, we propose here the use of nonparametric statistical procedures for diagnosis of the fingerprinting model, specifically: (1) A non parametric statistical test, based on paired bootstrap resampling, for comparison of different fingerprinting models; (2) New accuracy measurements (the uncertainty area and its bias) which take into account the complex nature of the fingerprinting output. The bootstrap comparison test and the accuracy measurements are used for RSS-IL in ourWiFi network, showing relevant information relating to the different fingerprinting schemes that can be
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.titleNonparametric Model Comparison and Uncertainty Evaluation for Signal Strength Indoor
dc.subject.unesco3325 Tecnología de las Telecomunicacioneses
dc.description.departamentoTeoría de la Señal y Comunicaciones

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Atribución-NoComercial-SinDerivadas 3.0 EspañaExcept where otherwise noted, this item's license is described as Atribución-NoComercial-SinDerivadas 3.0 España