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Extremely large-scale multiple-input multiple-output (XL-MIMO) is capable ofsupporting extremely high system capacities with large numbers of users. Inthis work, we build a framework for the analysis and low-complexity design ofXL-MIMO in the near field with spatial non-stationarities. Specifically, wefirst analyze the theoretical performance of discrete-aperture XL-MIMO using anelectromagnetic (EM) channel model based on the near-field spherical wavefront.We analytically reveal the impact of the discrete aperture and polarizationmismatch on the received power. We also complement the classical Fraunhoferdistance based on the considered EM channel model. Our analytical resultsindicate that a limited part of the XL-array receives the majority of thesignal 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 theacquired VR information to devise a low-complexity symbol detection scheme.Furthermore, we propose a graph theory-based user partition algorithm, relyingon the VR overlap ratio between different users. Partial zero-forcing (PZF) isutilized to eliminate only the interference from users allocated to the samegroup, which further reduces computational complexity in matrix inversion.Numerical results confirm the correctness of the analytical results and theeffectiveness of the proposed algorithms. It reveals that our algorithmsapproach the performance of conventional whole array (WA)-based designs butwith much lower complexity.

Performance Analysis and Low-Complexity Design for XL-MIMO with Near-Field Spatial Non-Stationarities