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Receiver Design for Massive MIMO Wireless Systems

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dc.contributor.advisor Tian, Zhi Xu, Ping
dc.creator Xu, Ping 2018-01-31 2019-09-12T19:51:48Z 2019-09-12T19:51:48Z
dc.description.abstract Massive multiple-input multiple-output (MIMO) systems that employ a large number of antennas at both receivers and transmitters have been widely considered for adoption in next generation (5G) wireless networks. The deployment of massive MIMO promises to enhance the received signal power for communications over millimeter-wave (mmWave) spectrum, which in turn increases the throughput and system efficiency. Notwithstanding the advantages of massive MIMO, several major technical challenges arise, which include the difficulty and complexity in hardware implementation, precoder design and channel estimation. In this thesis, we mainly focus on strategies that address the training overhead issue for mmWave massive MIMO channel estimation. By utilizing the sparsity feature in the angular domain of mmWave channels, we propose a gridless compressive sensing (CS) technique based on atomic norm minimization (ANM). Particularly for massive MIMO systems involving two-dimensional angle estimation, we develop a decoupled ANM (DANM) approach that offers high-accuracy channel estimation at low complexity and little training overhead. The proposed D-ANM approach is applied to mmWave massive MIMO systems with uniform rectangular array employed at base station and extended to the multiuser case. Investigation on the use of D-ANM for channel estimation in wideband mmWave SIMO-OFDM systems is also carried out to cope with frequency-selective channel fading.
dc.language.iso en en_US
dc.subject millimeter-wave massive MIMO en_US
dc.subject receiver design en_US
dc.subject OFDM en_US
dc.subject frequency-selective fading en_US
dc.subject atomic norm minimization en_US
dc.title Receiver Design for Massive MIMO Wireless Systems en_US
dc.type Thesis en_US Master of Science in Electrical and Computer Engineering en_US Master's en_US Electrical and Computer Engineering en_US George Mason University en_US

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