Impact of beacon coverage on clustering strategies for fingerprinting localization system

Among the various indoor localization systems, received signal strength (RSS) based fingerprinting localization provides most cost-effective solution as it uses the existing wireless network infrastructure. The positioning accuracy of such localization systems can be improved by incorporating huge number of training data, which in turn, increases the searching overhead of such localization systems. Several clustering strategies for fingerprinting localization have been proposed in literature in order to reduce the searching overhead. On the other hand, placement strategy of beacon nodes within the field of localization has significant influence on the performances of clustering strategies for fingerprinting localization. Two important factors associated with some beacon placement strategy are the degree of beacon coverage and the distribution of beacon nodes. In this paper, we present an optimal beacon placement strategy that meets a k-coverage visibility requirement for beacons at every point within the field of localization. Next, we demonstrate the impact of beacon coverage on the performance of several clustering strategies suitable for a large-scale fingerprinting localization system.