Different techniques of positioning users in cellular networks have been studied widely in recent years but there is no proper comparison of them, maybe that is because of their first step of geo-location, i.e., extracting location information parameters, is different and there is no unique simulation environment yet has been applied to them. In this study it is tried to have a new look to these positioning methods and to classify them differently regardless of estimated parameters type. Their classification is based on mathematical algorithms used to find user location in the both area of deterministic and stochastic approaches, these algorithms can then use with the same parameter so comparison between them is rational and possible. Such algorithms divided into three main subclasses, estimation theory based (MUSIC, ESPIRIT), Meta-heuristic (Genetic, PSO, ...) and filtering approaches (Kalman, Particle, Grid, MH ). To do the comparison, these methods should be developed according to the network assumptions and the proper simulation in the same environment is applied. The proofs and details of how to apply techniques are presented.
展开▼
