Coarsely quantized Massive MU-MIMO uplink with iterative decision feedback receiver

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dc.contributor.authorZhang, Zeyang
dc.contributor.supervisorMcGuire, Michael Liam
dc.date.accessioned2020-05-04T23:37:11Z
dc.date.available2020-05-04T23:37:11Z
dc.date.copyright2020en_US
dc.date.issued2020-05-04
dc.degree.departmentDepartment of Electrical and Computer Engineering
dc.degree.levelMaster of Applied Science M.A.Sc.en_US
dc.description.abstractMassive MU-MIMO (Multiuser-Multiple Input and Multple Output) is a promising technology for 5G wireless communications because of its spectrum and energy efficiency. To combat the distortion from multipath fading channel, the acquisition of channel state information is essential, which generally requires the training signal that lowers the data rate. In addition, coarse quantization can reduce the high computational energy and cost, yet results in the loss of information. In this thesis, an iterative decision feedback receiver, including iterative Channel Estimation (CE) and equalization, is constructed for a Massive MU-MIMO uplink system. The impact of multipath distortion and coarse quantization can be gradually reduced due to the iterative structure that exploits extrinsic feedback to improve the CE and data detection, so that the data rate is improved by reducing training signals for CE and by using low precision quantization. To observe and evaluate the convergence behaviour, an Extrinsic Information Transfer (EXIT) chart method is utilized to visualize the performance of the iterative receiver.en_US
dc.description.scholarlevelGraduateen_US
dc.identifier.urihttp://hdl.handle.net/1828/11719
dc.languageEnglisheng
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.subjectMassive MIMOen_US
dc.subjectcoarse quantizationen_US
dc.subjectiterative decision feedbacken_US
dc.subjectChannel Estimationen_US
dc.subjectZero-Forcing equalizationen_US
dc.subjectMMSE equalizationen_US
dc.subjectEXIT charten_US
dc.titleCoarsely quantized Massive MU-MIMO uplink with iterative decision feedback receiveren_US
dc.typeThesisen_US

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