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This paper considers the problem of fingerprinting localization in wireless networks based on received-signal-strength (RSS) observations. First, the performance of static localization using power maps (PMs) is improved with a new approach called the base-station-strict (BS-strict) methodology, which emphasizes the effect of BS identities in the classical fingerprinting. Second, dynamic motion models with and without road network information are used to further improve the accuracy via particle filters. The likelihood-calculation mechanism proposed for the particle filters is interpreted as a soft version (called BS-soft) of the BS-strict approach applied in the static case. The results of the proposed approaches are illustrated and compared with an example whose data were collected from a WiMAX network in a challenging urban area in the capitol city of Brussels, Belgium. [ABSTRACT FROM AUTHOR]

DVB-H networks allow high data rate broadcast access for hand-held terminals. Building penetration loss measurements of a DVB-H signal at 602 MHz are performed in 100 buildings in Belgium. Buildings are categorized in different types (office buildings, apartments, villas, mansions, row houses, stations) and the rooms are classified according to the number of outside radiated walls. The cumulative distribution function of the penetration loss is determined and lognormality is investigated. Models are developed to calculate the penetration loss as a function of the number of radiated walls. Also models for apartments as a function of the floor level are developed. This research enables the calculation of indoor coverage probability for wireless networks. [ABSTRACT FROM AUTHOR]