An analytical random direction-based method in user mobility modeling for wireless networks

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