{"title":"通过优化移动网络切换参数提高用户体验质量","authors":"R. Fang, Gang Chuai, Weidong Gao","doi":"10.1145/3424978.3425031","DOIUrl":null,"url":null,"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.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Improve Quality of Experience of Users by Optimizing Handover Parameters in Mobile Networks\",\"authors\":\"R. Fang, Gang Chuai, Weidong Gao\",\"doi\":\"10.1145/3424978.3425031\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":178822,\"journal\":{\"name\":\"Proceedings of the 4th International Conference on Computer Science and Application Engineering\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 4th International Conference on Computer Science and Application Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3424978.3425031\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3424978.3425031","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improve Quality of Experience of Users by Optimizing Handover Parameters in Mobile Networks
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.