QoE-driven resource allocation for mobile IP services in wireless network

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In this study, quality of experience(QoE)-driven resource allocation for multi-applications in Internet Protocol(IP)-based wireless networks is studied. Considering that the mean opinion score(MOS) summation maximization problem is not fair to satisfy heterogeneous users’ QoE with various mobile applications, we apply multi-objective optimization method to maximize each user’s MOS utility. At the beginning of this work, the relationship between MOS utility and user transmission rate for three multimedia applications, that is, File Download, Internet Protocol Television, and Voice over Internet Protocol are discussed. However, the relations under diverse evaluation models are quite different and users in various mobile applications have different requirements, which make the optimization problem difficult to solve. To meet each user’s minimum rate requirement,the idea of Nash bargaining solution is applied in the Hungarian-based subcarrier assignment problem. Then to simplify the power allocation problem, the concept of equivalent channel is introduced. Further by applying the tolerance membership function, we develop a fuzzy Max-Min decision model for generating an optimal power allocation solution. Simulation results demonstrate the satisfying characteristics of the proposed algorithm in terms of MOS utility and average data rate. In this study, quality of experience (QoE) -driven resource allocation for multi-applications in Internet Protocol (IP) -based wireless networks is studied. Considering that the mean opinion score (MOS) summation maximization problem is not fair to satisfy heterogeneous users At the beginning of this work, the relationship between MOS utility and user transmission rate for three multimedia applications, that is, File Download, Internet Protocol Television, and Voice over Internet Protocol are discussed. However, the relation under diverse evaluation models are quite different and users in various mobile applications have different requirements, which make the optimization problem difficult to solve. of Nash bargaining solution is applied in the Hungarian-based subcarrier assignment problem. Then to simplify the power allocation result, the concept of equivalent channel is introduced. Further by applying the tolerance membership function, we develop a fuzzy Max-Min decision model for generating an optimal power allocation solution. Simulation results demonstrate the satisfying characteristics of the proposed algorithm in terms of MOS utility and average data rate.
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