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dc.contributor.authorChen, Chih-Yuen_US
dc.contributor.authorWu, Wen-Rongen_US
dc.date.accessioned2019-04-02T05:59:38Z-
dc.date.available2019-04-02T05:59:38Z-
dc.date.issued2018-07-01en_US
dc.identifier.issn0018-9545en_US
dc.identifier.urihttp://dx.doi.org/10.1109/TVT.2018.2798360en_US
dc.identifier.urihttp://hdl.handle.net/11536/147882-
dc.description.abstractBeamforming with antenna arrays has been considered as an enabling technology in future wireless communication systems. To conduct beamforming, one has to know the angle-of-departure (AoD) or angle-of-arrival (AoA). For data detection, the receiver also has to know channel response. In this paper, we propose a new joint. AoD, AoA, and channel estimation scheme for pilot-assisted multiple-input-multiple-output orthogonal-frequency-division-multiplexing (MIMO-OFDM) systems. First, a compressive-sensing technique is employed to estimate the channel impulse response, exploiting the sparsity property of wireless channels. Then, AoA and AoD are jointly estimated for each detected path by the maximum likelihood method. The Cramer-Rao lower hound (CRLB) is also derived and a transmit beamforming scheme is proposed accordingly. In the scenario of available prior information, a maximum a posteriori estimation is proposed. The Bayesian CRLB (BCRLB) for the problem is also derived and a transmit beamforming scheme is further proposed. It turns out that only two training OFDM symbols are required for the estimation. Simulation results show that the proposed methods can approach the CRLB/BCRLB in both scenarios and achieve the same spectral efficiency as that obtained with the ideal channel in millimeter-wave communications.en_US
dc.language.isoen_USen_US
dc.subjectDigital communicationen_US
dc.subjectmaximum likelihood estimationen_US
dc.subjectmillimeter wave communicationen_US
dc.subjectmultiple-input-multiple-output (MIMO) systemsen_US
dc.subjectmultipath channelsen_US
dc.titleJoint AoD, AoA, and Channel Estimation for MIMO-OFDM Systemsen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/TVT.2018.2798360en_US
dc.identifier.journalIEEE TRANSACTIONS ON VEHICULAR TECHNOLOGYen_US
dc.citation.volume67en_US
dc.citation.spage5806en_US
dc.citation.epage5820en_US
dc.contributor.department電機工程學系zh_TW
dc.contributor.departmentDepartment of Electrical and Computer Engineeringen_US
dc.identifier.wosnumberWOS:000438907600022en_US
dc.citation.woscount0en_US
Appears in Collections:Articles