The extremely large-scale massive multiple-input multiple-output (XL-MIMO) has the potential to achieve boosted spectral efficiency and refined spatial resolution for future wireless networks. However, channel estimation for XL-MIMO is challenging since the large number of antennas results in high computational complexity with the near-field effect. In this letter, we propose a low-complexity sequential angle-distance channel estimation (SADCE) method for near-field XL-MIMO systems equipped with uniformly planar arrays (UPA). Specifically, we first successfully decouple the angle and distance parameters, which allows us to devise a two-dimensional discrete Fourier transform (2D-DFT) method for angle parameters estimation. Then, a low-complexity distance estimation method is proposed with a closed-form solution. Compared with existing methods, the proposed method achieves significant performance gain with noticeably reduced computational complexity.Numerical results verify the superiority of the proposed near-field channel estimation algorithm.

翻译：极端大规模多输入多输出（XL-MIMO）在提升未来无线网络频谱效率和空间分辨率方面具有巨大潜力。然而，XL-MIMO的信道估计面临挑战，因为天线数量庞大导致近场效应下的计算复杂度极高。本文针对配备均匀平面阵列（UPA）的近场XL-MIMO系统，提出一种低复杂度序贯角度-距离信道估计（SADCE）方法。具体而言，我们首先成功解耦角度与距离参数，并据此设计了一种基于二维离散傅里叶变换（2D-DFT）的角度参数估计方法。随后，提出一种具有闭式解的低复杂度距离估计算法。与现有方法相比，所提算法在显著降低计算复杂度的同时实现了性能增益。数值结果验证了所提近场信道估计算法的优越性。