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This paper presents a new scheme to estimate the user mobility by incorporating the aggregate history of mobile users and system parameters. With this approach, each user's position within the location area is differentiated by zone partition for more accurate prediction. In order to provide the flexibility of tradeoff between quality demand and computation complexity, the estimation is adjusted dynamically according to the constraint of prediction order. Then an adaptive algorithm is developed to predict the future position of mobile terminals in terms of location probabilities, while considering each terminal's movement direction, residence time, and path information. Simulation results demonstrate that the signaling cost for location tracking under delay bound is greatly reduced based on the estimated user mobility pattern.