Location estimation by fingerprinting in cellular networks

Abstract

Location based services have attracted too much attention recently due to the increasing number of new value-added services. Also, the requirement set by Federal Communications Commission (FCC) to locate emergency calls according to certain accuracy criteria has been the key factor for the development of location methods. Hence, location positioning has been a key research problem and numerous localization solutions have been proposed. These include technologies such as Cell ID, angle and time of arrival methods, statistical methods and fingerprinting methods. This paper proposes a fingerprinting based positioning method. Location fingerprinting is a novel method that benefits from the previous signal measurements to find the location of a user. The previous signal measurements are stored into a database, called fingerprint database, to be used for fingerprint matching. Fingerprinting consists of four phases such as data collection, fingerprint filtering, fingerprint matching, and location estimation algorithms. In this thesis, a new fingerprint matching algorithm is proposed to increase the accuracy of the location based services. This new fingerprint matching algorithm is compared with the most frequently used and well-known algorithms. The proposed algorithm does not require any hardware modifications. It does not require any modifications in the software on the mobile devices, either. By exploiting the measurements that are already being performed by the cellular network, the system can estimate the location of the mobile station using the RSS values of the MS. It is shown that the proposed algorithm gives better results than the compared algorithms in terms of accuracy.