Department of Computer Engineering & CITIC Research Center, University of A Coruña, Galicia 15001, Spain .
Sensors (Basel). 2020 Feb 10;20(3):930. doi: 10.3390/s20030930.
A method for channel estimation in wideband massive MIMO systems using hybrid digital analog architectures is developed. The proposed method is useful for FDD at either sub-6 GHz or mmWave frequency bands and takes into account the beam squint effect caused by the large bandwidth of the signals. To circumvent the estimation of large channel vectors, the posed algorithm relies on the slow time variation of the channel spatial covariance matrix, thus allowing for the utilization of very short training sequences. This is possibledue to the exploitation of the channel structure. After identifying the channel covariance matrix, the channel is estimated on the basis of the recovered information. To that end, we propose a novel method that relies on estimating the tap delays and the gains as sociated with each path. As a consequence, the proposed channel estimator achieves low computational complexity and significantly reduces the training overhead. Moreover, our numerical simulations show better performance results compared to the minimum mean-squared error solution.
提出了一种利用混合数字模拟架构的宽带大规模 MIMO 系统信道估计方法。该方法适用于 FDD 在 sub-6GHz 或毫米波频段，并考虑到信号大带宽引起的波束斜视效应。为了避免估计大的信道向量，所提出的算法依赖于信道空间协方差矩阵的慢时变，从而允许使用非常短的训练序列。这是由于信道结构的利用。在识别信道协方差矩阵之后，根据恢复的信息对信道进行估计。为此，我们提出了一种新的方法，该方法依赖于估计每个路径的抽头延迟和增益。因此，所提出的信道估计器实现了低计算复杂度，并显著降低了训练开销。此外，我们的数值模拟结果表明，与最小均方误差解决方案相比，该方法具有更好的性能。
