{"title":"异构无线网络的系统间切换决策模型","authors":"Topside E. Mathonsi, Okuthe P. Kogeda, T. Olwal","doi":"10.1109/OI.2018.8535951","DOIUrl":null,"url":null,"abstract":"The number of mobile users has exponentially grown over the past years, and these users have the desire of always being connected wirelessly at any time anywhere, to the best available network. The existence of Heterogeneous Wireless Networks (HWNs) allows mobile users to be always connected and have access to network services and applications. However, to provide seamless intersystem handover remains a challenge, since mobile users' still experience lengthy handover delay. This is mainly because, previously proposed handover algorithms fail to predict the future values of the received signal strength (RSS). This led to extensive handover delay due to lengthy handover discovery process. Furthermore, these previously proposed handover algorithms only expresses scales of relative comparison and do not deal with decision problems of fuzziness and uncertainty that comes with the use of multiple parameters. These handover algorithms have fixed weighting matrix and therefore, could not adapt to the change of the network conditions and user's preference. As a result, these handover algorithms still experience erroneous network selection. Consequently, in this paper, an intelligent Intersystem Handover (IH) algorithm was designed by integrating Grey Prediction Theory (GPT), Multiple-Attribute Decision Making (MADM), Fuzzy Analytic Hierarchy Process (FAHP) and Principal Component Analysis (PCA). Numerous computer simulation results confirmed that the proposed IH algorithm shortened handover delay as compared with Fuzzy Logic Based vertical handover (FLBVH) algorithm and Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm.","PeriodicalId":331140,"journal":{"name":"2018 Open Innovations Conference (OI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Intersystem Handover Decision Model for Heterogeneous Wireless Networks\",\"authors\":\"Topside E. Mathonsi, Okuthe P. Kogeda, T. Olwal\",\"doi\":\"10.1109/OI.2018.8535951\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The number of mobile users has exponentially grown over the past years, and these users have the desire of always being connected wirelessly at any time anywhere, to the best available network. The existence of Heterogeneous Wireless Networks (HWNs) allows mobile users to be always connected and have access to network services and applications. However, to provide seamless intersystem handover remains a challenge, since mobile users' still experience lengthy handover delay. This is mainly because, previously proposed handover algorithms fail to predict the future values of the received signal strength (RSS). This led to extensive handover delay due to lengthy handover discovery process. Furthermore, these previously proposed handover algorithms only expresses scales of relative comparison and do not deal with decision problems of fuzziness and uncertainty that comes with the use of multiple parameters. These handover algorithms have fixed weighting matrix and therefore, could not adapt to the change of the network conditions and user's preference. As a result, these handover algorithms still experience erroneous network selection. Consequently, in this paper, an intelligent Intersystem Handover (IH) algorithm was designed by integrating Grey Prediction Theory (GPT), Multiple-Attribute Decision Making (MADM), Fuzzy Analytic Hierarchy Process (FAHP) and Principal Component Analysis (PCA). Numerous computer simulation results confirmed that the proposed IH algorithm shortened handover delay as compared with Fuzzy Logic Based vertical handover (FLBVH) algorithm and Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm.\",\"PeriodicalId\":331140,\"journal\":{\"name\":\"2018 Open Innovations Conference (OI)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Open Innovations Conference (OI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/OI.2018.8535951\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Open Innovations Conference (OI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/OI.2018.8535951","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Intersystem Handover Decision Model for Heterogeneous Wireless Networks
The number of mobile users has exponentially grown over the past years, and these users have the desire of always being connected wirelessly at any time anywhere, to the best available network. The existence of Heterogeneous Wireless Networks (HWNs) allows mobile users to be always connected and have access to network services and applications. However, to provide seamless intersystem handover remains a challenge, since mobile users' still experience lengthy handover delay. This is mainly because, previously proposed handover algorithms fail to predict the future values of the received signal strength (RSS). This led to extensive handover delay due to lengthy handover discovery process. Furthermore, these previously proposed handover algorithms only expresses scales of relative comparison and do not deal with decision problems of fuzziness and uncertainty that comes with the use of multiple parameters. These handover algorithms have fixed weighting matrix and therefore, could not adapt to the change of the network conditions and user's preference. As a result, these handover algorithms still experience erroneous network selection. Consequently, in this paper, an intelligent Intersystem Handover (IH) algorithm was designed by integrating Grey Prediction Theory (GPT), Multiple-Attribute Decision Making (MADM), Fuzzy Analytic Hierarchy Process (FAHP) and Principal Component Analysis (PCA). Numerous computer simulation results confirmed that the proposed IH algorithm shortened handover delay as compared with Fuzzy Logic Based vertical handover (FLBVH) algorithm and Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm.