Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/3734
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dc.contributor.authorNakmouche M.F.-
dc.contributor.authorIdrees Magray M.-
dc.contributor.authorAllam A.M.M.A.-
dc.contributor.authorFawzy D.E.-
dc.contributor.authorLin D.B.-
dc.contributor.authorTarng J.-H.-
dc.date.accessioned2023-06-16T15:03:07Z-
dc.date.available2023-06-16T15:03:07Z-
dc.date.issued2021-
dc.identifier.isbn9.79E+12-
dc.identifier.urihttps://doi.org/10.23919/ISAP47258.2021.9614588-
dc.identifier.urihttps://hdl.handle.net/20.500.14365/3734-
dc.description2021 International Symposium on Antennas and Propagation, ISAP 2021 -- 19 October 2021 through 22 October 2021 -- 174855en_US
dc.description.abstractBased on low-cost PCB solution, an array antenna in packaging (AiP) dedicated for mmWave mobile systems is designed using machine learning. The proposed antenna operates at 28 GHz (26.5 - 29.5 GHz) with a gain ranging from 8 dB to 15 dB in the operating bandwidth. The development process of the proposed AiP is assisted by machine learning for prediction of the optimal radiating patch's length and width in terms of resonance frequency. © 2021 Taiwan Microwave Association.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2021 International Symposium on Antennas and Propagation, ISAP 2021en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectANNen_US
dc.subjectAntenna in Packaging (AiP)en_US
dc.subjectmachine learningen_US
dc.subjectmmWaveen_US
dc.subjectAntenna arraysen_US
dc.subjectCostsen_US
dc.subjectMachine learningen_US
dc.subjectMicrowave antennasen_US
dc.subjectMillimeter wavesen_US
dc.subjectOrganic pollutantsen_US
dc.subjectANNen_US
dc.subjectAntenna in packagingen_US
dc.subjectArray designen_US
dc.subjectArray-antennaen_US
dc.subjectLow cost antennaen_US
dc.subjectLow-costsen_US
dc.subjectMachine-learningen_US
dc.subjectMm wavesen_US
dc.subjectMobile systemsen_US
dc.subjectOperating bandwidthen_US
dc.subjectPolychlorinated biphenylsen_US
dc.titleLow-Cost Aip Array Design Using Machine Learning for Mmwave Mobile Systemsen_US
dc.typeConference Objecten_US
dc.identifier.doi10.23919/ISAP47258.2021.9614588-
dc.identifier.scopus2-s2.0-85123318219-
dc.authorscopusid57206657916-
dc.authorscopusid55582327600-
dc.authorscopusid23011278600-
dc.authorscopusid7403692642-
dc.authorscopusid6604045835-
dc.identifier.wosWOS:001081957900236-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityN/A-
dc.identifier.wosqualityN/A-
item.openairetypeConference Object-
item.grantfulltextreserved-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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