Abstract

As a measurement, quality of service (QoS) has been commonly taken into account in the traditional vertical handoff schemes for the heterogeneous wireless access networks. However, the QoS is not sufficient to correlate well with the user satisfaction. In this paper, quality of experience (QoE) is introduced into the decision mechanism of the vertical handoff and a random neural network -based QoE estimation is proposed to determine the correlation between the QoE and the QoS in the heterogeneous networks. In addition, a Q-learning-based vertical handoff algorithm, designated as a QoE-Q algorithm, is presented in order to maximize the QoE utility for users. It can be observed from the simulation results that the proposed method not only outperforms the existing schemes with enhanced call blocking probability and handoff dropping probability property but also obtains better QoE performance in the service charges and the terminal power consumption than other schemes.

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