Resource allocation in GMD and SVD-based MIMO system

A. Ahrens, Francisco Cano-Broncano, C. Benavente-Peces
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引用次数: 3

Abstract

Singular-value decomposition (SVD)-based multiple-input multiple output (MIMO) systems, where the whole MIMO channel is decomposed into a number of unequally weighted single-input single-output (SISO) channels, have attracted a lot of attention in the wireless community. The unequal weighting of the SISO channels has led to intensive research on bit- and power allocation even in MIMO channel situation with poor scattering conditions identified as the antennas correlation effect. In this situation, the unequal weighting of the SISO channels becomes even much stronger. In comparison to the SVD-assisted MIMO transmission, geometric mean decomposition (GMD)-based MIMO systems are able to compensate the drawback of weighted SISO channels when using SVD, where the decomposition result is nearly independent of the antennas correlation effect. The remaining interferences after the GMD-based signal processing can be easily removed by using dirty paper precoding as demonstrated in this work. Our results show that GMD-based MIMO transmission has the potential to significantly simplify the bit and power loading processes and outperforms the SVD-based MIMO transmission as long as the same QAM-constellation size is used on all equally-weighted SISO channels.
基于GMD和svd的MIMO系统资源分配
基于奇异值分解(SVD)的多输入多输出(MIMO)系统,将整个MIMO信道分解为多个不等权重的单输入单输出(SISO)信道,引起了无线界的广泛关注。由于SISO信道的加权不均匀,在散射条件较差(即天线相关效应)的MIMO信道中,位和功率分配问题也得到了广泛的研究。在这种情况下,SISO通道的不平等权重变得更加强烈。与奇异值分解辅助MIMO传输相比,基于几何平均分解(GMD)的MIMO系统能够弥补使用奇异值分解时加权SISO信道的缺点,分解结果几乎不受天线相关效应的影响。基于gmd的信号处理后的剩余干扰可以通过使用脏纸预编码很容易地去除。我们的研究结果表明,只要在所有等权重的SISO信道上使用相同的qam星座大小,基于gmd的MIMO传输就有可能显著简化比特和功率加载过程,并且优于基于svd的MIMO传输。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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