{"title":"Enhancing Near-Field Wireless Localization With LiDAR-Assisted RIS in Multipath Environments","authors":"Omar Rinch;Ahmed Elzanaty;Ahmad Alsharoa","doi":"10.1109/LWC.2023.3311730","DOIUrl":null,"url":null,"abstract":"In next-generation wireless networks that adopt millimeter-waves and large reconfigurable intelligent surfaces (RISs), the user is expected to be in the near-field region, where the widely adopted far-field algorithms based on far-field can yield low positioning accuracy. Also, the localization of user equipment (UE) becomes more challenging in multipath environments. In this letter, we propose a localization algorithm for a UE in the near-field of a RIS in multipath environments. The proposed scheme utilizes a light detection and ranging (LiDAR) to assist the UE positioning by providing geometric information about some of the scatterers in the environment. This information is fed to a sparse recovery algorithm to improve the localization accuracy of the UE by reducing the number of variables (i.e., angle of arrivals and distances) to be estimated. The numerical results show that the proposed scheme can improve the localization accuracy by 65% compared to the standard compressed sensing (CS) scheme.","PeriodicalId":13343,"journal":{"name":"IEEE Wireless Communications Letters","volume":"12 12","pages":"2168-2172"},"PeriodicalIF":4.6000,"publicationDate":"2023-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Wireless Communications Letters","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10239240/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
In next-generation wireless networks that adopt millimeter-waves and large reconfigurable intelligent surfaces (RISs), the user is expected to be in the near-field region, where the widely adopted far-field algorithms based on far-field can yield low positioning accuracy. Also, the localization of user equipment (UE) becomes more challenging in multipath environments. In this letter, we propose a localization algorithm for a UE in the near-field of a RIS in multipath environments. The proposed scheme utilizes a light detection and ranging (LiDAR) to assist the UE positioning by providing geometric information about some of the scatterers in the environment. This information is fed to a sparse recovery algorithm to improve the localization accuracy of the UE by reducing the number of variables (i.e., angle of arrivals and distances) to be estimated. The numerical results show that the proposed scheme can improve the localization accuracy by 65% compared to the standard compressed sensing (CS) scheme.
期刊介绍:
IEEE Wireless Communications Letters publishes short papers in a rapid publication cycle on advances in the state-of-the-art of wireless communications. Both theoretical contributions (including new techniques, concepts, and analyses) and practical contributions (including system experiments and prototypes, and new applications) are encouraged. This journal focuses on the physical layer and the link layer of wireless communication systems.