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首页> 外文期刊>Information Theory, IEEE Transactions on >Backing Off From Infinity: Performance Bounds via Concentration of Spectral Measure for Random MIMO Channels
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Backing Off From Infinity: Performance Bounds via Concentration of Spectral Measure for Random MIMO Channels

机译：摆脱无限：通过频谱测量的集中度限制随机MIMO信道的性能

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摘要

The performance analysis of random vector channels, particularly multiple-input-multiple-output (MIMO) channels, has largely been established in the asymptotic regime of large channel dimensions, due to the analytical intractability of characterizing the exact distribution of the objective performance metrics. This paper exposes a new nonasymptotic framework that allows the characterization of many canonical MIMO system performance metrics to within a narrow interval under finite channel dimensionality, provided that these metrics can be expressed as a separable function of the singular values of the matrix. The effectiveness of our framework is illustrated through two canonical examples. In particular, we characterize the mutual information and power offset of random MIMO channels, as well as the minimum mean squared estimation error of MIMO channel inputs from the channel outputs. Our results lead to simple, informative, and reasonably accurate control of various performance metrics in the finite-dimensional regime, as corroborated by the numerical simulations. Our analysis framework is established via the concentration of spectral measure phenomenon for random matrices uncovered by Guionnet and Zeitouni, which arises in a variety of random matrix ensembles irrespective of the precise distributions of the matrix entries.
机译：由于表征目标性能指标的精确分布的分析难点性，很大程度上已经在大通道尺寸的渐近状态下建立了随机矢量通道，尤其是多输入多输出（MIMO）通道的性能分析。本文揭示了一种新的非渐近框架，该框架允许在有限信道维数下的狭窄区间内表征许多规范MIMO系统性能指标，前提是这些指标可以表示为矩阵奇异值的可分离函数。我们通过两个典型的例子说明了我们框架的有效性。特别地，我们表征随机MIMO信道的互信息和功率偏移，以及来自信道输出的MIMO信道输入的最小均方估计误差。我们的结果导致在有限维范围内对各种性能指标进行简单，信息丰富和合理准确的控制，这在数值模拟中得到了证实。我们的分析框架是通过对Guionnet和Zeitouni所发现的随机矩阵的光谱测量现象的集中而建立的，这种现象出现在各种随机矩阵集合中，而与矩阵项的精确分布无关。

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