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dc.contributor.authorRezgui, Haithem
dc.contributor.authorRouissi, Fatma
dc.contributor.authorGhazel, Adel
dc.date.accessioned2018-11-23T09:26:53Z
dc.date.available2018-11-23T09:26:53Z
dc.date.issued2018-09cs
dc.identifier.citationRadioengineering. 2018 vol. 27, č. 3, s. 909-916. ISSN 1210-2512cs
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/137051
dc.description.abstractIn this paper, a novel method for reducing a Simplified Volterra Series (SVS) model size is proposed for GaN RF Power Amplifier (PA) Digital Predistorter (DPD) design. Using the SVS-modified model, the number of coefficients needed for the PA behavioral modeling and predistortion can be reduced by 60 % while maintaining acceptable performances. Simulation and implementation tests are performed for a Class AB GaN PA and Doherty GaN PA using a 20-MHz Long Term Evolution-Advanced (LTE-A) signal. The Adjacent Channel Power Ratio (ACPR) attains -40 dB and -41 dB for the Doherty and Class AB GaN PAs, respectively. The implementation complexity is also studied and the obtained results prove the capability of the proposed model to linearize PA using 3% of the Slice LUTs and 87% of the DSP48E1 available in the Xilinx Zynq-7000 FPGA.en
dc.formattextcs
dc.format.extent909-916cs
dc.format.mimetypeapplication/pdfen
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttps://www.radioeng.cz/fulltexts/2018/18_03_0909_0916.pdfcs
dc.rightsCreative Commons Attribution 4.0 International licenseen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectRF power amplifieren
dc.subjectdigital predistortion (DPD)en
dc.subjectsimplified Volterra seriesen
dc.subjectestimation algorithmsen
dc.subjectlook up table (LUT)en
dc.subjectleast squares algorithmsen
dc.titleDigital Predistorter Design Using a Reduced Volterra Model to Linearize GaN RF Power Amplifiersen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
dc.coverage.issue3cs
dc.coverage.volume27cs
dc.identifier.doi10.13164/re.2018.0909en
dc.rights.accessopenAccessen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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Except where otherwise noted, this item's license is described as Creative Commons Attribution 4.0 International license