A new model for indoor WLAN positioning system

Abstract : In this paper we attempt to answer the following question : how to deploy a WLAN in order to guarantee the requested Quality of Service (QoS) while reducing the location error ? Such a problem includes two aspects : WLAN planning and positioning error reduction. To provide users an optimal wireless access to their local network, WLAN planning not only consists in selecting a location for each transmitter and setting the parameters of all sites, but also acts on allocating one of the available frequencies to each Access Point (AP) configuration [1]. And toward the indoor positioning system, once the Received Signal Strengths (RSSs) from all visible APs are measured and inputted, the location is estimated and outputted using the RSS distribution and machine learning technique [2]. We propose a new approach where WLAN planning and positioning error reduction are modeled as an optimization problem and tackled together during WLAN planning process.