A generalized matrix-decomposition processor for joint MIMO transceiver design

Yu Chi Wu, Pei Yun Tsai

研究成果: 書貢獻/報告類型會議論文篇章同行評審

4 引文 斯高帕斯(Scopus)

摘要

A generalized matrix-decomposition processor is designed and implemented, which supports QR decomposition (QRD), eigenvalue decomposition (EVD), and geometric-mean decomposition (GMD), to accelerate computations in MIMO precoding/beamforming systems. The processor adopts memory-based architecture with 16 processing elements (PEs) each consisting of one CORDIC module. An improved GMD algorithm is proposed, which reduces 13.2% complexity and can be implemented by homogeneous CORDIC operations. The EVD adopts the Rayleigh quotient shift and deflation technique to accelerate convergence. The basis computations can be accomplished by mirrored operations during channel matrix decomposition. From the implementation results, the generalized processor achieves decomposition throughput of 10M, 0.99M, 2.96M matrixes per second for 4 × 4 complex QRD, EVD and GMD.

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主出版物標題2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁面1153-1157
頁數5
ISBN(電子)9781509041176
DOIs
出版狀態已出版 - 16 6月 2017
事件2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - New Orleans, United States
持續時間: 5 3月 20179 3月 2017

出版系列

名字ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN(列印)1520-6149

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???event.eventtypes.event.conference???2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017
國家/地區United States
城市New Orleans
期間5/03/179/03/17

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