Channel Estimation In Intelligent Reflecting Surfaces for 5G and Beyond

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dc.authoridKabalci, Yasin/0000-0003-1240-817X
dc.authoridMUTLU, URAL/0000-0003-2595-0531
dc.contributor.authorMutlu, Ural
dc.contributor.authorKabalci, Yasin
dc.date.accessioned2024-11-07T13:23:57Z
dc.date.available2024-11-07T13:23:57Z
dc.date.issued2022
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description4th IEEE Global Power, Energy and Communication Conference (IEEE GPECOM) -- JUN 14-17, 2022 -- Cappadocia, TURKEY
dc.description.abstractIntelligent Reflecting Surfaces (IRS) are constructed of multiple independently controllable passive Reflecting Elements (RE), which can change the phase and amplitude of the reflected signals so that the reflected signals can be combined in coherent manner to achieve beamforming. To facilitate beamforming, the channel coefficients of the incoming and outgoing channels need to be estimated. In this study, the Discrete Fourier Transform (DFT) based channel estimation method is applied to an IRS-assisted communication system implementing Fifth Generation (5G) Orthogonal Frequency Division Multiplexing (OFDM) waveform in order to observe the effectiveness of the estimation method. DFT-based channel estimation has the advantage of not using the whole OFDM symbol for pilot transmission, thus it can be performed while transmitting data. Therefore, the effects of multipath delay spread, the number of REs, and training sequence sparsity in the OFDM symbol are observed for different Signal-to-Noise Ratio (SNR) values with a direct path and without a direct path. The results show that delay spread has a significant effect on the performance and training sequence length can be reduced.
dc.description.sponsorshipIEEE,IEEE Ind Applicat Soc,IEEE Ind Elect Soc,IEEE Power & Energy Soc,IEEE Power Elect Soc,Nevsehir Haci Bektas Veli Univ,Univ Nova Lisboa,Univ Palermo
dc.identifier.doi10.1109/GPECOM55404.2022.9815683
dc.identifier.endpage590
dc.identifier.isbn978-1-6654-6925-8
dc.identifier.scopus2-s2.0-85134881844
dc.identifier.scopusqualityN/A
dc.identifier.startpage586
dc.identifier.urihttps://doi.org/10.1109/GPECOM55404.2022.9815683
dc.identifier.urihttps://hdl.handle.net/11480/13827
dc.identifier.wosWOS:000854056400101
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartof2022 Ieee 4th Global Power, Energy and Communication Conference (Ieee Gpecom2022)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241106
dc.subjectIRS
dc.subjectChannel Estimation
dc.subjectDFT
dc.subjectOFDM
dc.subjectMISO
dc.titleChannel Estimation In Intelligent Reflecting Surfaces for 5G and Beyond
dc.typeConference Object

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