Hybrid beamforming for millimeter wave communications

dc.contributor.authorZhan, Jinlong
dc.contributor.supervisorDong, Xiaodai
dc.date.accessioned2022-04-29T20:50:39Z
dc.date.available2022-04-29T20:50:39Z
dc.date.copyright2022en_US
dc.date.issued2022-04-29
dc.degree.departmentDepartment of Electrical and Computer Engineering
dc.degree.levelDoctor of Philosophy Ph.D.en_US
dc.description.abstractCommunications over millimeter wave (mmWave) frequencies is a key component of the fifth generation (5G) cellular networks due to the large bandwidth available at mmWave bands. Thanks to the short wavelength of mmWave bands, large antenna arrays (32 to 256 elements are common) can be mounted at the transceivers. The array sizes are typical of a massive MIMO communication system, which makes fully digital beamforming difficult to implement due to high power consumption and hardware cost. This motivates the development of hybrid beamforming due to its versatile tradeoff between implementation cost (including hardware cost and power consumption) and system performance. However, due to the non-convex constraints on hardware (phase shifters), finding the global optima for hybrid beamforming design is often intractable. In this thesis, we focus on hybrid beamforming design for mmWave cellular communications both narrowband and wideband scenarios are considered. Starting from narrowband SU-MIMO mmWave communications, we propose a Gram-Schmidt orthogonalization (GSO) aided hybrid precoding algorithm to reduce computation complexity. GSO is a recursive process that depends on the order in which the matrix columns are selected. A heuristic solution to the order of column selection is suggested according to the array response vector along which the full digital precoder has the maximum projection. The proposed algorithm, not only constrained to uniform linear arrays (ULAs), can avoid the matrix inversion in designing the digital precoder compared to the orthogonal matching pursuit (OMP) algorithm. For the narrowband MU-MIMO mmWave communications, we propose an interference cancellation (IC) framework on hybrid beamforming design for downlink mmWave multi-user massive MIMO system. Based on the proposed framework, three successive interference cancellation (SIC) aided hybrid beamforming algorithms are proposed to deal with inter-user and intra-user interference. Furthermore, the optimal detection order of data streams is derived according to the post-detection signal-to-interference- plus-noise ratio (SINR). When considering wideband MU-MIMO mmWave communications, how to design a common RF beamformer across all subcarriers becomes the main challenge. Furthermore, the common RF beamformer in wideband channels leads to the need of more effective baseband schemes. By adopting a relaxation of the original mutual information and spectral efficiency maximization problems at the transceiver, we design the radio frequency (RF) precoder and combiner by leveraging the average of the covariance matrices of frequency domain channels, then a SIC aided baseband precoder and combiner are proposed to eliminate inter-user and intra-user interferenceen_US
dc.description.scholarlevelGraduateen_US
dc.identifier.bibliographicCitationJinlong Zhan, Xiaodai Dong, Yiming Huo, and Yu Zhang. "Gram-Schmidt orthogonalisation aided hybrid precoding in millimeter-wave massive MIMO systems." IET Communications, vol. 14, no. 3 pp. 387-396, October 2019.en_US
dc.identifier.bibliographicCitationJinlong Zhan and Xiaodai Dong, "Interference Cancellation Aided Hybrid Beamforming for mmWave Multi-User Massive MIMO Systems," in IEEE Transactions on Vehicular Technology, vol. 70, no. 3, pp. 2322-2336, March 2021en_US
dc.identifier.urihttp://hdl.handle.net/1828/13914
dc.languageEnglisheng
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.subject5Gen_US
dc.subjectmmWave communicationsen_US
dc.subjectmassive MIMOen_US
dc.subjecthybrid beamformingen_US
dc.subjectinterference cancellationen_US
dc.titleHybrid beamforming for millimeter wave communicationsen_US
dc.typeThesisen_US

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