Accurate channel parameter estimation is challenging for wideband millimeter-wave (mmWave) large-scale hybrid arrays, due to beam squint and much fewer radio frequency (RF) chains than antennas. This article presents a novel joint angle and delay estimation (JADE) approach for wideband mmWave fully-connected hybrid uniform cylindrical arrays. We first design a new hybrid beamformer to reduce the dimension of received signals on the horizontal plane by exploiting the convergence of the Bessel function, and to reduce the active beams in the vertical direction through preselection. The important recurrence relationship of the received signals needed for subspace-based angle and delay estimation is preserved, even with substantially fewer RF chains than antennas. Then, linear interpolation is generalized to reconstruct the received signals of the hybrid beamformer, so that the signals can be coherently combined across the whole band to suppress the beam squint. As a result, efficient subspace-based algorithm algorithms can be developed to estimate the angles and delays of multipath components. The estimated delays and angles are further matched and correctly associated with different paths in the presence of non-negligible noises, by putting forth perturbation operations. Simulations show that the proposed approach can approach the Cramér-Rao lower bound (CRLB) of the estimation with a significantly lower computational complexity than existing techniques.

中文翻译：

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具有混合前端的毫米波圆柱阵列多径角和延迟的联合估计

由于波束斜视和比天线少得多的射频 (RF) 链，对于宽带毫米波 (mmWave) 大规模混合阵列而言，准确的信道参数估计具有挑战性。本文提出了一种用于宽带毫米波全连接混合均匀圆柱阵列的新型联合角度和延迟估计 (JADE) 方法。我们首先设计了一种新的混合波束形成器，通过利用贝塞尔函数的收敛性来减少水平面上接收信号的维度，并通过预选减少垂直方向的活动波束。即使 RF 链比天线少得多，基于子空间的角度和延迟估计所需的接收信号的重要递归关系也得以保留。然后，线性插值被推广到重构混合波束形成器的接收信号，以便信号可以在整个频带上相干组合以抑制波束斜视。因此，可以开发有效的基于子空间的算法算法来估计多径分量的角度和延迟。通过提出扰动操作，在存在不可忽略的噪声的情况下，估计的延迟和角度进一步匹配并与不同的路径正确关联。模拟表明，与现有技术相比，所提出的方法可以以显着降低的计算复杂度来逼近估计的克拉默-拉奥下界（CRLB）。可以开发有效的基于子空间的算法算法来估计多径分量的角度和延迟。通过提出扰动操作，在存在不可忽略的噪声的情况下，估计的延迟和角度进一步匹配并与不同的路径正确关联。模拟表明，与现有技术相比，所提出的方法可以以显着降低的计算复杂度来逼近估计的克拉默-拉奥下界（CRLB）。可以开发有效的基于子空间的算法算法来估计多径分量的角度和延迟。通过提出扰动操作，在存在不可忽略的噪声的情况下，估计的延迟和角度进一步匹配并与不同的路径正确关联。模拟表明，与现有技术相比，所提出的方法可以以显着降低的计算复杂度来逼近估计的克拉默-拉奥下界（CRLB）。