Schur Complement Based Analysis of MIMO Zero-Forcing for Rician Fading
Schur Complement Based Analysis of MIMO Zero-Forcing for Rician Fading
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DOI：
10.1109/twc.2014.2371467
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发表时间：
2014-01
影响因子：
10.4
通讯作者：
C. Siriteanu;A. Takemura;S. Kuriki;D. Richards;Hyundong Shin
中科院分区：
文献类型：
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作者：
C. Siriteanu;A. Takemura;S. Kuriki;D. Richards;Hyundong Shin
对于具有零强制检测（ZF）的多输入/多输出（MIMO）空间复用，信号衰落的信噪比（SNR）分析涉及传输样本相关（Gramian）矩阵的繁琐的非中心- wishart分布（NCWD）。以前使用虚拟CWD的近似方法可以得到ZF信噪比的近似（虚拟）Gamma分布。然而，确定信噪比分布近似精度的分析条件尚不清楚。因此，我们一直在尝试准确地表征ZF信噪比。我们之前的尝试仅仅是在ririan - rayleigh衰落下，通过将ZF信噪比写成grian中的标量舒尔补（SC），成功地处理了唯一的ririan -衰落流。在这里，我们追求一个更一般的基于矩阵sc的分析，以表征信噪比时，几个流可能会经历专家衰落。一方面，对于全梯度衰落，SC分布当且仅当信道均值相关条件成立时为CWD。有趣的是，这个CWD与由近似得到的虚CWD重合。因此，在这种情况下，实际信噪比和虚拟信噪比的分布是一致的。另一方面，对于ririan - rayleigh衰落，矩阵- sc分布是根据具有初等函数项的矩阵的行列式来表征的，这也产生了ZF信噪比的新表征。平均误差概率结果验证了我们的分析与模拟。
For multiple-input/multiple-output (MIMO) spatial multiplexing with zero-forcing detection (ZF), signal-to-noise ratio (SNR) analysis for Rician fading involves the cumbersome noncentral-Wishart distribution (NCWD) of the transmit sample-correlation (Gramian) matrix. An approximation with a virtual CWD previously yielded for the ZF SNR an approximate (virtual) Gamma distribution. However, analytical conditions qualifying the accuracy of the SNR-distribution approximation were unknown. Therefore, we have been attempting to exactly characterize ZF SNR for Rician fading. Our previous attempts succeeded only for the sole Rician-fading stream under Rician-Rayleigh fading, by writing the ZF SNR as scalar Schur complement (SC) in the Gramian. Herein, we pursue a more general matrix-SC-based analysis to characterize SNRs when several streams may undergo Rician fading. On one hand, for full-Rician fading, the SC distribution is found to be exactly a CWD if and only if a channel-mean-correlation condition holds. Interestingly, this CWD then coincides with the virtual CWD ensuing from the approximation. Thus, under the condition, the actual and virtual SNR-distributions coincide. On the other hand, for Rician-Rayleigh fading, the matrix-SC distribution is characterized in terms of the determinant of a matrix with elementary-function entries, which also yields a new characterization of the ZF SNR. Average error probability results validate our analysis vs. simulation.