We consider the uplink channel estimation problem in a millimeter wave (mmWave) system with large-scale antenna arrays. Unlike many existing works which estimate the channel assuming that the number of channel paths is known a priori, we address the problem of channel estimation with an unknown number of channel paths. The spatial channel is transformed into the beamspace channel by the discrete Fourier transform (DFT). Based on the sparsity property of the beamspace channel, we propose three algorithms to estimate the number of paths, direction of arrivals (DoAs) and path gains. The first one is the Spectrum Weighted Identification of Signal Sources (SWISS) for the case when the channel statistics are unknown, which introduces a weight vector to amplify the desired signal and suppress the noise. The second one is the Neyman-Pearson criterion based-Detector (NPD) based on the Rician channel model, which adopts the Neyman-Pearson criterion to decide whether there exists a path on each DFT point. In practice, the DoAs are continuously distributed, leading to the power leakage problem. We solve this leakage problem by proposing the combined algorithm with leakage (CAL). Simulation results show that the proposed algorithms perform better than the conventional spatial smoothing.

中文翻译：

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具有大规模天线阵列的毫米波系统中的信道路径识别

我们考虑具有大规模天线阵列的毫米波 (mmWave) 系统中的上行链路信道估计问题。与许多假设信道路径数量是先验已知的估计信道的现有工作不同，我们解决了信道路径数量未知的信道估计问题。空间通道通过离散傅立叶变换 (DFT) 转换为波束空间通道。基于波束空间信道的稀疏性，我们提出了三种算法来估计路径数、到达方向（DoAs）和路径增益。第一个是信号源频谱加权识别 (SWISS)，适用于信道统计数据未知的情况，它引入了一个权重向量来放大所需信号并抑制噪声。第二种是基于Rician信道模型的Neyman-Pearson准则的检测器（NPD），它采用Neyman-Pearson准则来判断每个DFT点上是否存在路径。实际上，DoA 是连续分布的，导致功率泄漏问题。我们通过提出带有泄漏（CAL）的组合算法来解决这个泄漏问题。仿真结果表明，所提出的算法性能优于传统的空间平滑。