A Comparison of Multiple Algorithms for Fingerprinting using IEEE802.11

The effectiveness of Location Based Systems depends on the correct location of users and mobile devices. While the outdoor location can be easily calculated, using technologies such as GPS (Global Positioning System), it is more difficult to obtain when the location scenario is an indoor environment. Several technologies and location techniques can be used in this field. One of these techniques is fingerprinting which consists in two different phases: the first phase is the calibration phase when data is collected and the Fingerprint Map is generated; the second phase is the on-line phase where data collected by the mobile device and the data collected in the calibration phase are used to estimate the location of the mobile node. From the several wireless communications technologies IEEE802.11 is probably the most used in Wireless Local Area Networks, so it was chosen for this work. In this paper a comparison between different type of Location Estimation Algorithms is presented: Nearest Neighbour, k-Nearest Neighbour, Weighted k-Nearest Neighbour and an algorithm based on Fuzzy Logic. For these tests three different mobile terminals where used, two mobile phones and one laptop computer. In these tests Fuzzy Logic had the best precision when the terminal used to do the location is not the same used to do the Fingerprint Map. It also had the lower standard deviation for all the test cases. The values of precision and standard deviation, as expected, are dependent on the type of terminal used to do the location.