Mobile Base Station Position Estimation Using Real Measurements Collected by Smart Phones

The mobile operators aim to have always updated information about the coverage areas of the mobile network, the changes that happen to the channel conditions and the environmental changes (e.g. new buildings) around the nodes of their mobile network. Extracting such information by analyzing the collected data from the current mobile network is one of the research topics that attract the researcher recently. Such information is helping the mobile operators to efficiently optimize and reconfigure their network to fulfill the user's needs. The Base Transceiver Station (BTS) position is one example of information which can be extracted from the collected data. In this Master thesis, two techniques based on Linear Algebra concepts are introduced to estimate the BTS position. First technique estimates the BTS position by solving a system of non-linear equations using the Linear Least Square Estimator (LLSE). With the second technique, the BTS position is estimated by solving a system of linear equations by the same estimator. Both Techniques are tested using artificial data in error-free data and erroneous data scenarios. Afterwards, the techniques are evaluated using real data collected by "Nexus 5" smart phone using the "Mesuradio" Android-App tool. Comparison between the performances of the two techniques is carried out. The experiments' results show how both techniques help to estimate the position of the BTS.