当前位置: X-MOL 学术EURASIP J. Adv. Signal Process. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
A robust LU polynomial matrix decomposition for spatial multiplexing
EURASIP Journal on Advances in Signal Processing ( IF 1.7 ) Pub Date : 2020-11-10 , DOI: 10.1186/s13634-020-00705-3
Moustapha Mbaye , Moussa Diallo , Mamadou Mboup

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.



中文翻译:

用于空间复用的鲁棒LU多项式矩阵分解

本文利用基于LU的多项式矩阵分解,考虑了MIMO宽带系统中的时域空间复用。与基于QR的空间多路复用方法相比,由于相应的前置和后置滤波器不是超ary元的,因此会放大噪声输出功率,并降低系统的性能。降级很重要,因为后置滤波器多项式矩阵条件不佳。在本文中,我们对分解进行了简单的转换,以解决不良条件问题。我们表明,这导致了对噪声和信道估计误差具有鲁棒性的MIMO空间复用方案。在后一种情况下,就复杂性和误码率而言,所建议的基于LU的波束成形与基于QR的波束成形相比具有优势。

更新日期:2020-11-12
down
wechat
bug