Extremely large-scale multiple-input multiple-output (XL-MIMO) promises to provide ultrahigh data rates in millimeter-wave (mmWave) and Terahertz (THz) spectrum. However, the spherical-wavefront wireless transmission caused by large aperture array presents huge challenges for channel state information (CSI) acquisition and beamforming. Two independent parameters (physical angles and transmission distance) should be simultaneously considered in XL-MIMO beamforming, which brings severe overhead consumption and beamforming degradation. To address this problem, we exploit the near-field channel characteristic and propose two low-overhead hierarchical beam training schemes for near-field XL-MIMO system. Firstly, we project near-field channel into spatial-angular domain and slope-intercept domain to capture detailed representations. Then we point out three critical criteria for XL-MIMO hierarchical beam training. Secondly, a novel spatial-chirp beam-aided codebook and corresponding hierarchical update policy are proposed. Thirdly, given the imperfect coverage and overlapping of spatial-chirp beams, we further design an enhanced hierarchical training codebook via manifold optimization and alternative minimization. Theoretical analyses and numerical simulations are also displayed to verify the superior performances on beamforming and training overhead.

翻译：[译摘要] 超大规模多输入多输出（XL-MIMO）有望在毫米波（mmWave）和太赫兹（THz）频段提供超高速数据传输。然而，大孔径阵列引起的球面波前无线传输给信道状态信息（CSI）获取和波束赋形带来巨大挑战。XL-MIMO波束赋形需同时考虑两个独立参数（物理角度与传输距离），导致严重的开销负担和波束赋形性能损失。针对这一问题，本文利用近场信道特性，提出了两种面向近场XL-MIMO系统的低开销分层波束训练方案。首先，将近场信道投影至空间-角度域和斜率-截距域以获取精细表示，并指出XL-MIMO分层波束训练的三项关键准则。其次，提出新型空间啁啾波束辅助码本及其对应的分层更新策略。再次，针对空间啁啾波束覆盖不完善和重叠问题，通过流形优化与交替最小化方法进一步设计增强型分层训练码本。理论分析与数值仿真验证了所提方案在波束赋形性能和训练开销方面的优越性。