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首页> 外文期刊>IEEE transactions on wireless communications >Low-Complexity Sorted QR Decomposition for MIMO Systems Based on Pairwise Column Symmetrization
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Low-Complexity Sorted QR Decomposition for MIMO Systems Based on Pairwise Column Symmetrization

机译:基于成对列对称的MIMO系统低复杂度排序QR分解

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摘要

QR decomposition (QRD) is a preprocessing technique for detecting symbols in multiple-input and multiple-output (MIMO) systems, but the computational complexity is prohibitively high when the systems incorporate a large number of antennas. This paper presents a low-complexity sorted QRD (SQRD) algorithm for MIMO systems. The proposed algorithm performs SQRD through orthogonalizations based on the modified Gram-Schmidt process, rearranging the column vectors of a real-valued MIMO channel matrix in such a way that the symmetry between the vectors is maintained. By using the symmetry, the computations required for orthogonalizing one of the two adjacent vectors can be eliminated effectively, which significantly reduces the computational complexity. Theoretical analyses show that the proposed algorithm reduces the computational complexity required for SQRD by 50% for any MIMO configurations, when compared to the conventional algorithm. In addition, the memory requirement to store resultant matrices is 50% of that in the conventional one.
机译:QR分解(QRD)是一种用于在多输入多输出(MIMO)系统中检测符号的预处理技术,但是当系统中包含大量天线时,计算复杂度将过高。本文提出了一种用于MIMO系统的低复杂度排序QRD(SQRD)算法。所提出的算法基于改进的Gram-Schmidt过程通过正交化执行SQRD,以保持向量之间的对称性的方式重新排列实值MIMO信道矩阵的列向量。通过使用对称性,可以有效地消除正交化两个相邻向量之一所需要的计算,这大大降低了计算复杂度。理论分析表明,与传统算法相比,对于任何MIMO配置,该算法将SQRD所需的计算复杂度降低了50%。另外,存储结果矩阵的存储需求是传统存储需求的50%。

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