Reduced-complexity SVD with adjustable accuracy for precoding in large-scale MIMO systems

Pei Yun Tsai, Chin Yi Liu

研究成果: 書貢獻/報告類型會議論文篇章同行評審

6 引文 斯高帕斯(Scopus)

摘要

Singular value decomposition (SVD) plays an important role for MIMO precoding. To reduce the complexity of precoding based on SVD for large-scale MIMO systems, we first analyze the impact of SVD accuracy to the system performance and derive the error tolerance regarding the constellation, target bit error rate, and the number of transmitted spatial streams. Then, to perform SVD with given accuracy, aggressive split/deflation in the Golub-Reinsch (GR) SVD algorithm is adopted for finding the singular values. Furthermore, the shifted QR algorithm with the early termination mechanism is proposed to obtain only the desired singular vectors instead of all the singular vectors. Finally, we show that the aggressive split/deflation and early termination are effective, especially to process the correlated channel matrixes. The proper threshold setting can maintain the system performance with only tiny degradation. Compared to Golub-Reinsch (GR) SVD, the proposed scheme can achieve 15%∼60% complexity reduction.

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主出版物標題Electronic Proceedings of the 2015 IEEE International Workshop on Signal Processing Systems, SiPS 2015
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781467396042
DOIs
出版狀態已出版 - 2 12月 2015
事件IEEE International Workshop on Signal Processing Systems, SiPS 2015 - Hangzhou, China
持續時間: 14 10月 201516 10月 2015

出版系列

名字IEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation
2015-December
ISSN(列印)1520-6130

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???event.eventtypes.event.conference???IEEE International Workshop on Signal Processing Systems, SiPS 2015
國家/地區China
城市Hangzhou
期間14/10/1516/10/15

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