Implementation of Neural Network Adaptive Digital Pre-distortion for Wireless Transmitters

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dc.contributor.advisorGhannouchi, Fadhel M.
dc.contributor.authorHasan, Md Mahmud
dc.date.accessioned2015-11-19T16:38:49Z
dc.date.embargolift2017-11-18T16:38:49Z
dc.date.issued2015-11-19
dc.date.submitted2015en
dc.description.abstractAn Artificial Neural Network, more precisely Real Valued Spatiotemporal Neural Network (RVSNN) based real time adaptive digital pre-distorter (DPD) is proposed and implemented on FPGA for the linearization of nonlinear dynamic wireless transmitter. Power amplifier is the core component of wireless transmitter, and is the source of all the nonlinearities and distortions. To alleviate these distortions, DPD, designed based on the inverse characteristics of power amplifier, is the key technology in 3G and beyond wireless communications. Though off-line DPD ameliorates system performance considerably, it is still dependent on changes in system temperature, voltage, load mismatch and average signal power. In this regard, real time DPD provides increased stability along with the standard linearity and inter-modulation distortion requirements. But the proposed online RVSNN model is very sensitive to hardware delay and hard to realize, thus offline RVSNN model is implemented on FPGA which provides identical performance to its MATLAB counterpart.en_US
dc.description.embargoterms2 yearsen_US
dc.identifier.citationHasan, M. M. (2015). Implementation of Neural Network Adaptive Digital Pre-distortion for Wireless Transmitters (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/26468en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/26468
dc.identifier.urihttp://hdl.handle.net/11023/2646
dc.language.isoeng
dc.publisher.facultyGraduate Studies
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectEngineering--Electronics and Electrical
dc.subject.classificationADAPTIVE DIGITAL PRE-DISTORTIONen_US
dc.subject.classificationNEURAL NETWORK PRE-DISTORTIONen_US
dc.titleImplementation of Neural Network Adaptive Digital Pre-distortion for Wireless Transmitters
dc.typemaster thesis
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.item.requestcopytrue
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