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dc.contributor.authorLin, Chun-Taoen_US
dc.contributor.authorWu, Wen-Rongen_US
dc.date.accessioned2014-12-08T15:26:39Z-
dc.date.available2014-12-08T15:26:39Z-
dc.date.issued2010en_US
dc.identifier.isbn978-1-4244-8016-6en_US
dc.identifier.urihttp://hdl.handle.net/11536/18943-
dc.identifier.urihttp://dx.doi.org/10.1109/PIMRC.2010.5671891en_US
dc.description.abstractPrecoding is an effective method to improve the transmission quality in multiple-input multiple-output (MIMO) systems. In a real-world system, the precoder is selected from a codebook, and its index is fed back to the transmitter. For a maximum-likelihood (ML) receiver, the criterion for precoder selection is equivalent to maximizing the minimum distance of the received signal constellation. T he derivation of the optimum solution, however, may be of high computational complexity due to the requirement of the exhaustive search. To reduce the computational complexity, a suboptimum solution based on singular value decomposition (SVD) has been proposed in literature. In this paper, we propose using a QR decomposition (QRD) based method for precoder selection. To further improve the system performance, we also propose an enhanced QRD-based selection method. With Givens rotations, the computational complexity of the enhanced QRD-based method can be effectively reduced. Finally, we combine precoding with receive antenna selection, and use the proposed QRD-based methods to solve this joint optimization problem. Simulation results show that the proposed approaches can significantly improve the system performance.en_US
dc.language.isoen_USen_US
dc.titleQRD-based Precoder Selection for Maximum-likelihood MIMO Detectionen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1109/PIMRC.2010.5671891en_US
dc.identifier.journal2010 IEEE 21ST INTERNATIONAL SYMPOSIUM ON PERSONAL INDOOR AND MOBILE RADIO COMMUNICATIONS (PIMRC)en_US
dc.citation.spage455en_US
dc.citation.epage460en_US
dc.contributor.department電機工程學系zh_TW
dc.contributor.departmentDepartment of Electrical and Computer Engineeringen_US
dc.identifier.wosnumberWOS:000305822600082-
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