A Comparison of Pedestrian Mobility Prediction Schemes in Wireless Cellular Networks

ABSTRACT: As the number of mobile technology users in wireless cellular communication increases everyday, the quality of service (QoS) concerns are not totally satisfied. Mobile users are not limited to a fixed location and can move around to other places. Mobility model is a method which is used to predict future location of a mobile user using different techniques. Mobility model is one approach for solving the mobility problem to guarantee the QoS. In this thesis, we compare two different mobility models for pedestrian movements through simulation using two actual trajectory datasets in the same area with different arrival rates. The first model is called current mobility parameters method, which predicts the future position of mobile user based on current parameters such as current location information, speed and direction. This information is mostly gathered using a positioning system such as GPS. Gauss-Markov mobility model predicts next location using current speed, direction and location information of the user. The second method is called observation histories method, in which prediction is performed based on the historical movement pattern of the user. For this model, a simple second order Markov-Mobility model predicts next position using current and one previous location information of that user. The simulation result shows that the observation histories method has a better performance than the current mobility parameters method for pedestrian movement. The precision rate for current mobility parameters was 99.74 % for first and second dataset, respectively and 99.88 % and 99.87% for observation histories method. Keywords: Wireless Cellular Network, QoS, Mobility Prediction, Path Prediction, Mobility Model, User Mobility, Next Location Prediction. …………………………………………………………………………………………………………………………