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dc.contributor.authorMahdi, Hasan F.
dc.contributor.authorAlheety, Ahmed T.
dc.contributor.authorHamid, Nather A.
dc.contributor.authorKurnaz, Sefer
dc.date.accessioned2021-05-15T12:49:27Z
dc.date.available2021-05-15T12:49:27Z
dc.date.issued2021
dc.identifier.issn1937-8718
dc.identifier.urihttps://doi.org/10.2528/PIERC20102306
dc.identifier.urihttps://hdl.handle.net/20.500.12939/1015
dc.description2-s2.0-85103279168en_US
dc.description.abstractUsing multiple-Input Multiple-Output (MIMO) configuration is not new in the field of wireless communication to increase the capacity of the system. This configuration is still valid to use nowadays with the modern wireless configuration such as the Fifth generation (5G). Massive MIMO is the key resource of the 5G systems due to its huge ability to increase the capacity of the network and on the other hand its ability to enhance both spectral and transmit-energy efficiency. The need for using Massive MIMO comes from the increase in using smartphones, tablets, and the rise of the Internet of Things. This increasing demand for the use of wireless applications requires networking and Internet infrastructures to meet the needs of current and future multimedia applications which massive MIMO satisfies. The key limitation of using massive MIMO is the cost of installation of these antennas and how to multiplex between them. In addition to this, the Radio Frequency (RF) links are also increased where this increase leads to high system complexity and hardware energy consumption. Because of this, reducing the required number of RF chains is essential to use by performing antenna selection which this paper aims to evaluate without significant performance loss which can be performed by employing low-resolution Analog-to-Digital Converter (ADC) to select an antenna with the best tradeoff between the additional channel gain and increase in quantization error. In this paper, Quantization-Aware Greedy Antenna Selection (QAGAS) algorithm has been proposed and compared with other antenna selection algorithms especially simple algorithms like random selection and Fast Antenna Selection (FAS) algorithm. The achieved capacity is compared with that of a very simple scheme that selects the antennas with the highest received power. The system capacity obtained from QAGAS is evaluated related to the transmit power of the Base Station (BS) and the quantization bits used in the lowresolution ADC. The simulation is also performed for a different numbers of users served by the BS and with the number of antennas at the BS. The simulation results show that the proposed algorithm indicates a potential for significant reductions of massive MIMO implementation complexity, by reducing the number of RF links and performing antenna selection using simple algorithms. © 2021, Electromagnetics Academy. All rights reserved.en_US
dc.language.isoengen_US
dc.publisherElectromagnetics Academyen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectMIMOen_US
dc.subjectQAGASen_US
dc.subjectQAFASen_US
dc.titleQuantization-aware greedy antenna selection for multi-user massive MIMO systemsen_US
dc.typearticleen_US
dc.departmentMühendislik ve Doğa Bilimleri Fakültesi, Elektrik ve Bilgisayar Mühendisliği Bölümüen_US
dc.department-tempMahdi, H.F., Faculty of Electrical and Computer Engineering, Altınbaş University, Turkey; Alheety, A.T., Department of Communication Technical Engineering, College of Engineering Techniques, Al-Farahidi University, Iran; Hamid, N.A., Faculty of Electrical and Computer Engineering, Altınbaş University, Turkey; Kurnaz, S., Faculty of Electrical and Computer Engineering, Altınbaş University, Turkeyen_US
dc.contributor.institutionauthorKurnaz, Sefer
dc.contributor.institutionauthorHamid, Nather A.
dc.identifier.doi10.2528/PIERC20102306
dc.identifier.volume111en_US
dc.identifier.startpage15en_US
dc.identifier.endpage24en_US
dc.relation.journalProgress In Electromagnetics Research Cen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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