{"title":"A Genetic Algorithm Approach to User Location Estimation in UMTS Networks","authors":"M.J. Magro, C. J. Debono","doi":"10.1109/EURCON.2007.4400320","DOIUrl":null,"url":null,"abstract":"An innovative solution to user location estimation in 3G networks is presented. The proposed solution uses network information such as Cell-ID and transmitted signal strength, which are easily captured by current 3G mobile handsets, as input to a location detection algorithm which searches the whole network coverage area for the most probable point of origin. This search is performed within a software model of the radio network, which faithfully replicates the provider's live network. The algorithm was optimized through the application of a genetic algorithm to provide an estimate of the user's location in quasi real-time. Simulation results demonstrate that allowing for a 450 m error, the algorithm is capable of locating the user's position in 72% of the cases within an urban environment.","PeriodicalId":191423,"journal":{"name":"EUROCON 2007 - The International Conference on \"Computer as a Tool\"","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"EUROCON 2007 - The International Conference on \"Computer as a Tool\"","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EURCON.2007.4400320","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
An innovative solution to user location estimation in 3G networks is presented. The proposed solution uses network information such as Cell-ID and transmitted signal strength, which are easily captured by current 3G mobile handsets, as input to a location detection algorithm which searches the whole network coverage area for the most probable point of origin. This search is performed within a software model of the radio network, which faithfully replicates the provider's live network. The algorithm was optimized through the application of a genetic algorithm to provide an estimate of the user's location in quasi real-time. Simulation results demonstrate that allowing for a 450 m error, the algorithm is capable of locating the user's position in 72% of the cases within an urban environment.