Joint Channel Estimation and Localization in RIS Assisted OFDM-MIMO System

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dc.authoridMUTLU, URAL/0000-0003-2595-0531
dc.contributor.authorMutlu, Ural
dc.contributor.authorBilim, Mehmet
dc.contributor.authorKabalci, Yasin
dc.date.accessioned2025-02-24T17:18:31Z
dc.date.available2025-02-24T17:18:31Z
dc.date.issued2024
dc.departmentFakülteler, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü
dc.description6th Global Power -- Energy and Communication Conference (GPECOM) -- JUN 04-07 -- 2024 -- Budapest -- HUNGARY
dc.description.abstractReconfigurable Intelligent Surfaces (RISs) are expected to become one of the enabling technologies in the development of the sixth generation (6G) smart radio environment, where services such as localization and sensing are going to be ubiquitous and an integral part of the system. However, achieving localization in a dense urban environment is a challenging task. Therefore, this study considers joint channel and localization estimation in a RIS-assisted orthogonal frequency division multiplexing multiple-input multiple-output (OFDM-MIMO) system operating in a dense urban environment, where only Non-Line-of-Sight (NLoS) multipath components are available. The channel estimation is based on the channels being sparse in the spatial and angular domains and having only a few Angles of Arrival (AoA) and Angles of Departure (AoD), thus the channel estimation becomes a sparse signal recovery problem that can be solved with compressive sensing algorithms. The study implements Simultaneous Orthogonal Matching Pursuit (SOMP) to obtain AoA and AoD. The time delay parameters are obtained by correlating OFDM subcarriers with a search matrix. A localization estimation algorithm based on linearization of the estimated geometric parameters is adopted. The results of the study show that for a channel consisting of 3 NLoS paths, location estimation in the range of decimeters is possible.
dc.description.sponsorshipIEEE
dc.identifier.doi10.1109/GPECOM61896.2024.10582646
dc.identifier.endpage692
dc.identifier.isbn979-8-3503-5108-8
dc.identifier.isbn979-8-3503-5109-5
dc.identifier.issn2832-7667
dc.identifier.scopus2-s2.0-85199021685
dc.identifier.scopusqualityN/A
dc.identifier.startpage687
dc.identifier.urihttps://doi.org/10.1109/GPECOM61896.2024.10582646
dc.identifier.urihttps://hdl.handle.net/20.500.14440/727
dc.identifier.wosWOS:001268516300068
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartofProceedings 2024 Ieee 6th Global Power, Energy and Communication Conference, Ieee Gpecom 2024
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250201
dc.subjectChannel Estimation
dc.subjectCompressive Sensing
dc.subjectLocalization
dc.subjectReconfigurable Intelligent Surface
dc.subjectSOMP
dc.titleJoint Channel Estimation and Localization in RIS Assisted OFDM-MIMO System
dc.typeConference Object

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