Effect of Mobility Prediction on Resource Utilization in Wireless Networks

Abstract

Mobile wireless network performance, measured using throughput, call blocking and dropping probabilities and resource utilization, is related to the mobility behavior of users. Statistical information pertaining to user mobility can be exploited to design mobility aware networks. This paper proposes a mobile network design method using prior mobility data. The mobility prediction scheme proposed is based on the well known Hidden Markov Model (HMM). This model is incorporated into a control theoretic framework that uses mobility history in the feedback loop to optimally allocate network resources to user sessions. The model and framework are validated via extensive Simulink Control System toolbox and MATLAB simulations. Simulation results show the effectiveness of the approach in improving network resource utilization and significantly reducing call dropping probability. It is also observed that the approach is scalable in the number of network users.

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