Extremely large-scale multiple-input multiple-output (XL-MIMO) is capable of supporting extremely high system capacities with large numbers of users. In this work, we build a framework for the analysis and low-complexity design of XL-MIMO in the near field with spatial non-stationarities. Specifically, we first analyze the theoretical performance of discrete-aperture XL-MIMO using an electromagnetic (EM) channel model based on the near-field spherical wavefront. We analytically reveal the impact of the discrete aperture and polarization mismatch on the received power. We also complement the classical Fraunhofer distance based on the considered EM channel model. Our analytical results indicate that a limited part of the XL-array receives the majority of the signal power in the near field, which leads to a notion of visibility region (VR) of a user. Thus, we propose a VR detection algorithm and leverage the acquired VR information to devise a low-complexity symbol detection scheme. Furthermore, we propose a graph theory-based user partition algorithm, relying on the VR overlap ratio between different users. Partial zero-forcing (PZF) is utilized to eliminate only the interference from users allocated to the same group, which further reduces computational complexity in matrix inversion. Numerical results confirm the correctness of the analytical results and the effectiveness of the proposed algorithms. It reveals that our algorithms approach the performance of conventional whole array (WA)-based designs but with much lower complexity.

中文翻译：

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具有近场空间非平稳性的 XL-MIMO 性能分析和低复杂度设计


超大规模多输入多输出（XL-MIMO）能够支持具有大量用户的极高系统容量。在这项工作中，我们构建了一个用于空间非平稳性近场 XL-MIMO 分析和低复杂度设计的框架。具体来说，我们首先使用基于近场球面波前的电磁（EM）信道模型分析离散孔径 XL-MIMO 的理论性能。我们分析揭示了离散孔径和偏振失配对接收功率的影响。我们还基于考虑的 EM 通道模型补充了经典的夫琅和费距离。我们的分析结果表明，XL 阵列的有限部分接收了近场中的大部分信号功率，这导致了用户可见区域 (VR) 的概念。因此，我们提出了一种 VR 检测算法，并利用获取的 VR 信息来设计一种低复杂度的符号检测方案。此外，我们提出了一种基于图论的用户划分算法，依赖于不同用户之间的VR重叠率。利用部分迫零（PZF）仅消除分配到同一组的用户的干扰，这进一步降低了矩阵求逆的计算复杂度。数值结果验证了分析结果的正确性和所提算法的有效性。它表明我们的算法接近传统的基于全阵列（WA）的设计的性能，但复杂性要低得多。