ISSN(Online): 2320-9801 ISSN (Print): 2320-9798 International Journal of Innovative Research in Computer and Communication Engineering (An ISO 3297: 2007 Certified Organization) Vol. 1, Issue 10, December 2013 Copyright to IJIRCCE www.ijircce.com 2282 Indoor Positioning Using the Modified Fingerprint Technique Carlos Kornuta 1 , Nelson Acosta 2 , Juan Toloza 3 CONICET, INCA/INTIA - School of Exact Sciences – UNICEN, Tandil, Argentina 1 INCA/INTIA - School of Exact Sciences – UNICEN, Tandil, Argentina 2 CONICET, INCA/INTIA - School of Exact Sciences – UNICEN, Tandil, Argentina 3 ABSTRACT: The Wi-Fi positioning systems available for enclosed spaces use the existing network infrastructure to calculate the position of the mobile device (MD). The most commonly used parameter is RSSI (Received Signal Strength Indicator). In this paper, we analyze the Fingerprint technique considering some variations aimed at improving the accuracy of the technique and minimizing calculation time. Significant field work is carried out, analyzing the accuracy achieved with each technique. Keywords: Indoor positioning, Wireless LAN, RSSI, Fingerprint. I. INTRODUCTION Location Based Services (LBS) allow obtaining information about the mobile device (MD) in relation to references on a predefined space [1]. In this sense, positioning systems that are based on Wi-Fi signals have gained great significance in recent years because they allow calculating the position using an already-existing infrastructure in most buildings and public places, meaning that the installation of no additional hardware is required on the MDs, since most of them already offer access to Wi-Fi connections. The techniques used to calculate a position in an enclosed space are classified, based on the sensor technology used, in: Time of Arrival (ToA), Angle of Arrival (AoA), and Received Signal Strength Indicator (RSSI). In the case of RSSI, there are two main models used to calculate the position of the MD: signal propagation model and empirical model. The former is based on the application of mathematical models that determine signal behavior and its degradation while it propagates. The empirical model calculates the position based on parameters that are stored in a database. Within the latter, the algorithm that is most widely used for calculating positions is the Fingerprint algorithm [2] [5]. The Fingerprint technique is the most widely used technique nowadays, due to its high degree of accuracy and its low implementation costs. These systems offer an accuracy of 2-3 meters in enclosed spaces, and 10 meters in outdoor areas [3] [4]. Several developments have been carried out in the area of device location using RSSI, and the Fingerprint technique in particular. One of the first approaches is the RADAR system [6], which combines two methods – an empirical model using Fingerprint and a mathematical model that takes into account signal propagation. The system obtains a mean accuracy within 2-3 meters. In [7], the authors of the RADAR system implement improvements, such as multipath and interference, with the purpose of analyzing and reducing problems that are inherent to the nature of the signal. They also analyze environmental changes during the experimental phase. The accuracy obtained is less than 2 meters. In 2003, the LEASE system [8] offers a framework based on the Fingerprint technique that achieves an accuracy of 2.1 m. The Ekahau commercial system [9] is a positioning software that consists in an administrator, a server, and a client. The administrator records the strength of the signal at the access points (APs), and creates the positioning