Heuristic inspired precoding for millimeter-wave MIMO systems with lens antenna subarrays

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dc.authorid0000-0001-9474-7372
dc.contributor.authorÇetinkaya, Şinasi
dc.contributor.authorAfeef, Liza
dc.contributor.authorMumcu, Gökhan
dc.contributor.authorArslan, Hüseyin
dc.date.accessioned2022-10-03T13:42:18Z
dc.date.available2022-10-03T13:42:18Z
dc.date.issued2022
dc.departmentİstanbul Medipol Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümü
dc.description.abstractA traditional array (TA) multiple-input multiple-output (MIMO) architecture in mmWave with hybrid beamforming suffers from high power consumption and hardware overhead. Therefore, a lens antenna subarray (LAS)-MIMO architecture has been recently proposed as a promising technology for a power-efficient system and reducing hardware cost and complexity. Additionally, the LAS-MIMO can offer spectral efficiency (SE) performance close to TA-MIMO and higher than single-lens antenna array (SLA)-MIMO. In this paper, we propose a hybrid precoding algorithm for the LAS-MIMO in mmWave to efficiently control the LAS design. The precoding problem is formulated as a sparse reconstruction problem due to the sparse behavior of mmWave channel. The proposed algorithm is an iterative process developed jointly using artificial bee colony (ABC) optimization with orthogonal matching pursuit (OMP) algorithms. In each iteration, the algorithm first selects the switches for each lens randomly using ABC and then uses OMP to approximate optimal unconstrained precoders. This process continues until achieving maximum SE. The simulation results show that LAS has around a 30% increase in SE compared to SLA while providing a significant gain in energy efficiency (EE) for single radio-frequency (RF) chain and multi RF chain scenarios.
dc.description.sponsorshipHuawei ; Nokia ; Pix Moving ; Samsung ; Technology Innovation Institute (TII)en_US
dc.identifier.citationÇetinkaya, Ş., Afeef, L., Mumcu, G. ve Arslan, H. (2022). Heuristic inspired precoding for millimeter-wave MIMO systems with lens antenna subarrays. IEEE 95th Vehicular Technology Conference: (VTC-Spring). Helsinki, 19-22 June 2022. https://dx.doi.org/10.1109/VTC2022-Spring54318.2022.9861021
dc.identifier.doi10.1109/VTC2022-Spring54318.2022.9861021
dc.identifier.isbn9781665482431
dc.identifier.issn1550-2252
dc.identifier.scopus2-s2.0-85137746953
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://dx.doi.org/10.1109/VTC2022-Spring54318.2022.9861021
dc.identifier.urihttps://hdl.handle.net/20.500.12511/9785
dc.identifier.wos000861825803061en_US
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorAfeef, Liza
dc.institutionauthorArslan, Hüseyin
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ecinfo:eu-repo/grantAgreement/EC/FP7/ECCS-1923857
dc.relation.ispartofIEEE 95th Vehicular Technology Conference: (VTC-Spring)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/embargoedAccess
dc.subjectArtificial Bee Colony Optimization
dc.subjectBasis Pursuit
dc.subjectLens Antenna Subarray
dc.subjectMIMO
dc.subjectPrecoding
dc.titleHeuristic inspired precoding for millimeter-wave MIMO systems with lens antenna subarrays
dc.typeConference Object

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