Performance Analysis of Polynomial Matrix SVD-Based Broadband MIMO Systems

André Sandmann, A. Ahrens, S. Lochmann
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引用次数: 4

Abstract

Singular-value decomposition (SVD) is well-established in multiple-input multiple-output (MIMO) signal processing where a broadband MIMO channel is transformed into a number of weighted single-input single-output (SISO) channels. However, applying SVD to frequency-selective MIMO channels results in unequally weighted SISO channels requiring complex resource allocation techniques for optimizing the channel performance. Therefore, a different approach utilizing polynomial matrix singular-value decomposition (PMSVD) for removing the MIMO interference is studied, outperforming conventional SVD-based MIMO systems in the analyzed channel scenarios. As shown by the bit-error rate (BER) simulation results as well as the obtained spectral efficiencies, the proposed PMSVD-based solution seems to be a good alternative to conventional SVD-based MIMO systems.
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基于多项式矩阵svd的宽带MIMO系统性能分析
奇异值分解(SVD)在多输入多输出(MIMO)信号处理中得到了广泛的应用,将一个宽带MIMO信道转化为多个加权单输入单输出(SISO)信道。然而,将奇异值分解应用于频率选择性MIMO信道会导致加权不均匀的SISO信道,需要复杂的资源分配技术来优化信道性能。因此,研究了一种利用多项式矩阵奇异值分解(PMSVD)去除MIMO干扰的方法,该方法在分析的信道场景中优于传统的基于奇异值分解的MIMO系统。误码率(BER)仿真结果和频谱效率表明,基于pmsvd的MIMO方案似乎是传统基于svd的MIMO系统的一个很好的替代方案。
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