In this study, we propose an improved channel estimator based on vector approximate message passing (VAMP) for quantized millimeter wave (mmWave) massive multiple-input and multiple-output (MIMO) systems. Using channel sparsity and the orthogonality of steering matrix, the proposed VAMP-on method designed for the on-grid scenario not only improves estimation performance but also has better convergence and inverse-free implementation. Furthermore, to achieve better estimation performance under the off-grid scenario, we provide a VAMP-off algorithm to update steering matrix and channel coefficients in an alternating fashion. Finally, simulation results are provided to demonstrate the advantages of the proposed approaches.

中文翻译：

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一种用于上行链路量化大规模 MIMO 系统的基于 VAMP 的广义信道估计器

在本研究中，我们针对量化毫米波 (mmWave) 大规模多输入多输出 (MIMO) 系统提出了一种基于矢量近似消息传递 (VAMP) 的改进信道估计器。利用信道稀疏性和导向矩阵的正交性，所提出的为并网场景设计的 VAMP-on 方法不仅提高了估计性能，而且具有更好的收敛性和无逆实现。此外，为了在离网场景下获得更好的估计性能，我们提供了一种 VAMP-off 算法来以交替方式更新导向矩阵和信道系数。最后，提供了仿真结果来证明所提出方法的优点。