A robust LU polynomial matrix decomposition for spatial multiplexing

Abstract This paper considers time-domain spatial multiplexing in MIMO wideband system, using an LU-based polynomial matrix decomposition. Because the corresponding pre- and post-filters are not paraunitary, the noise output power is amplified and the performance of the system is degraded, compared...

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Bibliographic Details
Main Authors: Moustapha Mbaye, Moussa Diallo, Mamadou Mboup
Format: Article
Language:English
Published: SpringerOpen 2020-11-01
Series:EURASIP Journal on Advances in Signal Processing
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Online Access:http://link.springer.com/article/10.1186/s13634-020-00705-3
Description
Summary:Abstract This paper considers time-domain spatial multiplexing in MIMO wideband system, using an LU-based polynomial matrix decomposition. Because the corresponding pre- and post-filters are not paraunitary, the noise output power is amplified and the performance of the system is degraded, compared to QR-based spatial multiplexing approach. Degradations are important as the post-filter polynomial matrix is ill-conditioned. In this paper, we introduce simple transformations on the decomposition that solve the ill-conditioning problem. We show that this results in a MIMO spatial multiplexing scheme that is robust to noise and channel estimation errors. In the latter context, the proposed LU-based beamforming compares favorably to the QR-based counterpart in terms of complexity and bit error rate.
ISSN:1687-6180