Simulation Based Comparison of Geo-Location Methods in Wireless Networks

There are many Geo-Location techniques proposed in cellular networks. They are mainly classified based on the parameters used to extract location information. In this study it is tried to have a new look to these positioning methods and to classify them differently regardless of parameters type. We classified these techniques base on mathematical algorithms which is used to derive location information of users in the network. Such algorithms are divided into three main subclasses in here, estimation theory based (MUSIC, ESPIRIT), Metaheuristic (Genetic, PSO...) and filtering approaches (Kalman, Particle, Grid, MH ). The proofs and details of how to apply techniques are presented and the simulation results are given.