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Estimation of Wideband Dynamic mmWave and THz Channels for 5G Systems and Beyond
IEEE Journal on Selected Areas in Communications ( IF 16.4 ) Pub Date : 2020-09-01 , DOI: 10.1109/jsac.2020.3000889
Alessandro Brighente , Mattia Cerutti , Monica Nicoli , Stefano Tomasin , Umberto Spagnolini

Millimeter wave (mmWave) wideband channels in a multiple-input multiple-output (MIMO) transmission are described by a sparse set of impulse responses in the angle-delay, or space-time (ST), domain. These characteristics will be even more prominent in the THz band used in future systems. We consider two approaches for channel estimation: compressed-sensing (CS), exploiting the sparsity in the angular/delay domain, and low-rank (LR), exploiting the algebraic structure of channel matrix. Both approaches share several commonalities, and this paper provides for the first time i) a comparison of the two approaches, and ii) new versions of CS and LR methods that significantly improve performance in terms of mean squared error (MSE), computational complexity, and latency. We derive the asymptotic MSE bound for any estimator of the ST-MIMO multipath channels with invariant angles/delays and time-varying fading, with unknown angle/delay diversity order: the bound also accounts for the degradation introduced by sub-optimal separable channel models. We will show that in the considered scenarios both CS and LR approaches attain the bound. Our performance assessment over ideal and $3^{rd}$ generation partnership project (3GPP) channel models, suitable for the fifth-generation (5G) and beyond of cellular networks, shows the trade-off obtained by the methods over various metrics: i) CS methods are converging faster than the LR methods, both attaining the asymptotic MSE bound; ii) the CS methods depend on the array manifold, while LR methods are independent of the array calibration; iii) CS solutions are more complex than LR solutions.

中文翻译:

估计 5G 系统及以后的宽带动态毫米波和太赫兹信道

多输入多输出 (MIMO) 传输中的毫米波 (mmWave) 宽带信道由角度延迟或时空 (ST) 域中的一组稀疏脉冲响应描述。这些特性在未来系统中使用的太赫兹频段中将更加突出。我们考虑了两种信道估计方法:压缩感知 (CS),利用角度/延迟域中的稀疏性,以及低秩 (LR),利用信道矩阵的代数结构。这两种方法有几个共同点,本文首次提供了 i) 两种方法的比较,以及 ii) 新版本的 CS 和 LR 方法,它们在均方误差 (MSE)、计算复杂度、和延迟。我们推导出具有不变角度/延迟和时变衰落的 ST-MIMO 多径信道的任何估计器的渐近 MSE 界限,角度/延迟分集阶数未知:该界限还解释了次优可分离信道模型引入的退化. 我们将证明,在考虑的场景中,CS 和 LR 方法都达到了界限。我们对适用于第五代 (5G) 及以后蜂窝网络的理想和 $3^{rd}$ 代合作伙伴项目 (3GPP) 信道模型的性能评估显示了通过各种指标获得的方法的权衡: ) CS 方法比 LR 方法收敛得更快,两者都达到了渐近 MSE 界限;ii) CS 方法依赖于阵列流形,而 LR 方法与阵列校准无关;
更新日期:2020-09-01
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