Sensing matrix design for wideband channel estimation in millimeter-wave hybrid multiple-input multiple-output system,Transactions on Emerging Telecommunications Technologies

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Sensing matrix design for wideband channel estimation in millimeter-wave hybrid multiple-input multiple-output system
Transactions on Emerging Telecommunications Technologies ( IF 2.5 ) Pub Date : 2022-09-01 , DOI: 10.1002/ett.4639
Amirhossein Molazadeh ₁ , Mehrdad Ardebilipour ₁ , Zahra Maroufi ₁

Affiliation

Hybrid analog/digital multiple-input multiple-output (MIMO) system is proposed to support low complexity multi-stream communication in millimeter-wave (mmWave) frequencies. The main idea of channel estimation methods for mmWave hybrid MIMO systems is based on leveraging the sparsity nature of the channel in the angle and delay domain. Sparse signal recovery algorithms have been used to reconstruct the channel coefficients. Due to the lack of information about the angle of arrival and angle of departure before channel estimation, random values are common choices for precoders and combiners. Moreover, the training pilot symbols are considered to be random variables. In this article, we propose sequential time domain sensing matrix design and sequential frequency domain sensing matrix design algorithms to design these variables in order to enhance sparse signal recovery performance and consequently the channel estimation accuracy. Our methods are based on reducing the correlation between the sensing matrix columns, which is defined in the sparse formulation of the channel estimation problem. We design the training radio frequency precoders/combiners phase angle values and pilot symbol vectors with the aid of a sequential procedure that has a reasonable complexity. Simulation results show that utilizing the designed values instead of random variables increased the performance of the channel estimation, especially when we deal with a higher number of variables.

中文翻译：

毫米波混合多输入多输出系统中宽带信道估计的传感矩阵设计

提出了混合模拟/数字多输入多输出 (MIMO) 系统，以支持毫米波 (mmWave) 频率下的低复杂度多流通信。毫米波混合 MIMO 系统的信道估计方法的主要思想是基于在角度和延迟域中利用信道的稀疏性。稀疏信号恢复算法已被用于重建信道系数。由于在信道估计之前缺乏关于到达角和离开角的信息，随机值是预编码器和组合器的常见选择。此外，训练导频符号被认为是随机变量。在本文中，我们提出时序时域感知矩阵设计和时序频域感知矩阵设计算法来设计这些变量，以提高稀疏信号恢复性能，从而提高信道估计精度。我们的方法基于减少传感矩阵列之间的相关性，这是在信道估计问题的稀疏公式中定义的。我们借助具有合理复杂性的顺序程序设计训练射频预编码器/组合器相角值和导频符号向量。仿真结果表明，使用设计值而不是随机变量可以提高信道估计的性能，尤其是当我们处理更多变量时。

更新日期：2022-09-01

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