Resource reservation in wireless networks based on pattern recognition

Resource reservation is very important for handoff control in wireless networks. Many researches have aimed to predict the user´s destination cell based on its movement pattern for efficient resource reservation. In the future networks with small size cells, handoffs will occur more frequently and the user´s movement will be more like a random process, so it is not practical to predict the accurate destination of a user. We propose a statistical strategy for resource reservation through the estimation of a user´s transfer probabilities, which represent the possibilities of the user leaving the current cell and entering the neighboring cells. The resources reserved for a user in each base station are proportional to the user´s transfer probabilities. A mathematical model is proposed to obtain the transfer probabilities of a user from the initial states (position, velocity and direction) through simulation of the user´s movement. Neural networks are developed to predict the transfer probabilities of a user from the initial states and facilitate efficient resource reservation