Abstract
An improvement to outdoor fingerprint location estimation based on clustering received signal strength (RSS) from base stations (BSs) is presented. The novel features that contribute to the greater accuracy are the use of deviations from the path loss model for each RSS component rather than the raw RSS for clustering; the accurate estimation of the cluster membership probability; the optimized trade-off between cluster size and accuracy of cluster modeling; and clusters are invariant to the BS or relay station (RS) power.
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