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首页> 外文期刊>Information Theory, IEEE Transactions on >A Central Limit Theorem for the SINR at the LMMSE Estimator Output for Large-Dimensional Signals
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A Central Limit Theorem for the SINR at the LMMSE Estimator Output for Large-Dimensional Signals

机译：LMMSE估计器输出中用于大尺寸信号的SINR的中心极限定理

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摘要

This paper is devoted to the performance study of the linear minimum mean squared error (LMMSE) estimator for multidimensional signals in the large-dimension regime. Such an estimator is frequently encountered in wireless communications and in array processing, and the signal-to-interference-plus-noise ratio (SINR) at its output is a popular performance index. The SINR can be modeled as a random quadratic form which can be studied with the help of large random matrix theory, if one assumes that the dimension of the received and transmitted signals go to infinity at the same pace. This paper considers the asymptotic behavior of the SINR for a wide class of multidimensional signal models that includes general multiple-antenna as well as spread-spectrum transmission models.
机译：本文致力于在大维状态下多维信号的线性最小均方误差（LMMSE）估计器的性能研究。在无线通信和阵列处理中经常遇到这样的估计器，并且其输出处的信号干扰加噪声比（SINR）是受欢迎的性能指标。如果假设接收和发送信号的维数以相同的速度达到无穷大，则可以将SINR建模为随机二次形式，可以借助大型随机矩阵理论进行研究。本文考虑了包括通用多天线以及扩频传输模型在内的多种多维信号模型的SINR的渐近行为。

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