In mobile communications, mobility modeling is involved in several aspects such as signaling and traffic load analysis. In particular, the accuracy of mobility models become essential for the evaluation of system design alternatives and network implementation cost issues. In this paper, we propose a mobility model which is appropriate for the practical analysis of the full range of mobile communications design issues. The model provides different levels of details for the user mobility behavior and can be adapted to any environment topology. This random direction based model can be applied in analytical purpose. This model is described by motion direction and user velocity. The motion direction of users is related to real street patterns and is modeled by discrete time and discrete state Gauss Markov. The velocity of users is modeled as Gaussian with variable mean and variance with respect to traffic factor. Simulation results confirm the preferences of the proposed method in both simulation and analytical estimations.

In mobile communications, mobility modeling is involved in several aspects such as signaling and traffic load analysis. In particular, accuracy of mobility models become essential for the evaluation of system design alternatives and network implementation cost issues. In thispaper wepropose a new method in which many important issues such as streets topology and traffic conditions are considered to model the user movement in a real environment. By using this model we also propose a new intelligent algorithm based on a sub-optimum path finding method tofind a properpath between source and destination. Theproposed model is suitablefor modification for random waypoint model and can be applied in mobile network simulation and intelligent transport system control.