Improve Quality of Experience of Users by Optimizing Handover Parameters in Mobile Networks

R. Fang, Gang Chuai, Weidong Gao
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引用次数: 1

Abstract

As the demand for mobile services grows exponentially, the focus on wireless network optimization has been changed from Quality of Service (QoS) for the network to Quality of Experience (QoE) for users. The network optimization research about QoS in the past cannot surely meet the requirements of the users' QoE. Therefore, in this paper, a handover solution is proposed to improve the QoE while considering the QoE balance for a LTE network that provides different services. Compared with other optimization of QoE nowadays, the proposed solution balances and improves the QoE of users. The proposed solution controls handover parameter by running a handover optimization algorithm based on the dynamic particle swarm optimization (DPSO) in a central controller, which finally optimizes the overall QoE and reduces the proportion of users with extremely poor QoE. The simulation results show that the DPSO algorithm ensures the quality of the solution and increases the speed of convergence by nearly twice that of the standard particle swarm optimization algorithm (SPSO). After adopting the DPSO handover solution, the overall QoE of users is increased by 6.22 % and 4.59 % while the variance of users' QoE is decreased by 14.2 % and 22.6 %, compared with the full handover solution and the traditional handover solution respectively. The number of users with QoE less than 1.9 is reduced to 0 with the proposed solution.
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通过优化移动网络切换参数提高用户体验质量
随着移动业务需求呈指数级增长,无线网络优化的重点已经从网络的服务质量(QoS)转向用户的体验质量(QoE)。以往关于QoS的网络优化研究肯定不能满足用户对QoS的要求。因此,本文在考虑不同业务的LTE网络的QoE平衡的同时,提出了一种切换方案来提高QoE。与目前其他的QoE优化方案相比,该方案平衡并提高了用户的QoE。该方案通过在中心控制器上运行基于动态粒子群优化(DPSO)的切换优化算法来控制切换参数,最终优化整体QoE,降低QoE极差用户的比例。仿真结果表明,DPSO算法在保证解质量的同时,收敛速度比标准粒子群优化算法(SPSO)提高了近2倍。采用DPSO切换方案后,用户总体QoE比完全切换方案和传统切换方案分别提高了6.22%和4.59%,用户QoE方差分别降低了14.2%和22.6%。在提出的解决方案下,QoE小于1.9的用户数量减少到0。
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