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

Massive 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. / Graduate

Identiferoai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/11719
Date04 May 2020
CreatorsZhang, Zeyang
ContributorsMcGuire, Michael Liam
Source SetsUniversity of Victoria
LanguageEnglish, English
Detected LanguageEnglish
TypeThesis
Formatapplication/pdf
RightsAvailable to the World Wide Web

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