Modeling and Mitigation of Nonlinear Distortions by using Neural Networks for LTE-A Wireless Transmitters

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atmire.migration.oldid4092
dc.contributor.advisorGhannouchi, Fadhel
dc.contributor.authorWang, Dongming
dc.contributor.committeememberBelostotski, Leonid
dc.contributor.committeememberHelaoui, Mohamed
dc.contributor.committeememberZareipour, Hamidreza
dc.date.accessioned2016-01-26T21:38:07Z
dc.date.available2016-01-26T21:38:07Z
dc.date.issued2016-01-26
dc.date.submitted2016en
dc.description.abstractA two-box DPD system based on the cascade of a memory predistortion model and a memoryless predistortion model is proposed. The memory predistortion model is designed by using an ARVTDNN, while the memoryless predistortion model is designed by using a memoryless ARVTDNN. Considering the signal at the output of the PA linearized by the proposed two-box DPD system, one will notice that its ACPR is demonstrated by measurement results to have a better performance by 3-5 dB than that of an existing two-box polynomial-based DPD system. Most importantly, the two-box polynomial-based DPD system does not meet the spectrum emission mask of -45 dBc. In addition, the proposed two-box ARVTDNN-based DPD system meets the ACPR requirements for the observation bandwidth of as low as 155 MHz.en_US
dc.identifier.citationWang, D. (2016). Modeling and Mitigation of Nonlinear Distortions by using Neural Networks for LTE-A Wireless Transmitters (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/26939en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/26939
dc.identifier.urihttp://hdl.handle.net/11023/2775
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
dc.subjectEngineering--Electronics and Electrical
dc.subject.classificationpower amplifier, modern communication systems, neural networks, digital predistortionen_US
dc.titleModeling and Mitigation of Nonlinear Distortions by using Neural Networks for LTE-A 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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