{"title":"An Effective User Localization and Environment Reconstruction Algorithm for WiFi Systems","authors":"Yuan Tang, Zhihai Zhang, Xinhong Pan, Heyun Lin, Yuan Chen","doi":"10.1109/ICCT56141.2022.10072501","DOIUrl":null,"url":null,"abstract":"Due to the cost-effective and easy-to-deploy characteristics, WiFi has been widely used in indoor localization. For millimeter wave (mmWave) WiFi indoor communication systems, we develop a two-stage algorithm to achieve user localization and environment reconstruction in this paper. In the first stage, accurate estimation of parameters as well as the reconstructed sparse signal can be obtained through the improved orthogonal matching pursuit (IOMP) algorithm. In second stage, we construct the geometric model of positions, and implement user localization and scattering environment mapping via computation combined with the estimated parameters. The proposed algorithm has low complexity and requires a small number of sub-carriers to realize user localization and environment reconstruction. Simulations verify the effectiveness of the proposed algorithm.","PeriodicalId":294057,"journal":{"name":"2022 IEEE 22nd International Conference on Communication Technology (ICCT)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 22nd International Conference on Communication Technology (ICCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCT56141.2022.10072501","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Due to the cost-effective and easy-to-deploy characteristics, WiFi has been widely used in indoor localization. For millimeter wave (mmWave) WiFi indoor communication systems, we develop a two-stage algorithm to achieve user localization and environment reconstruction in this paper. In the first stage, accurate estimation of parameters as well as the reconstructed sparse signal can be obtained through the improved orthogonal matching pursuit (IOMP) algorithm. In second stage, we construct the geometric model of positions, and implement user localization and scattering environment mapping via computation combined with the estimated parameters. The proposed algorithm has low complexity and requires a small number of sub-carriers to realize user localization and environment reconstruction. Simulations verify the effectiveness of the proposed algorithm.