Future sixth-generation (6G) systems are expected to leverage extremely large-scale multiple-input multiple-output (XL-MIMO) technology, which significantly expands the range of the near-field region. While accurate channel estimation is essential for beamforming and data detection, the unique characteristics of near-field channels pose additional challenges to the effective acquisition of channel state information. In this paper, we propose a novel codebook design, which allows efficient near-field channel estimation with significantly reduced codebook size. Specifically, we consider the eigen-problem based on the near-field electromagnetic wave transmission model. Moreover, we derive the general form of the eigenvectors associated with the near-field channel matrix, revealing their noteworthy connection to the discrete prolate spheroidal sequence (DPSS). Based on the proposed near-field codebook design, we further introduce a two-step channel estimation scheme. Simulation results demonstrate that the proposed codebook design not only achieves superior sparsification performance of near-field channels with a lower leakage effect, but also significantly improves the accuracy in compressive sensing channel estimation.

翻译：未来第六代（6G）系统预计将采用超大规模多输入多输出（XL-MIMO）技术，该技术显著扩展了近场区域的范围。尽管精确的信道估计对于波束赋形和数据检测至关重要，但近场信道的独特特性为信道状态信息的有效获取带来了额外挑战。本文提出了一种新型码本设计，能够在显著减小码本尺寸的同时实现高效的近场信道估计。具体而言，我们基于近场电磁波传输模型考虑了特征值问题。此外，我们推导了与近场信道矩阵相关的特征向量的通用形式，揭示了它们与离散椭球序列（DPSS）之间的显著关联。基于所提出的近场码本设计，我们进一步引入了一种两步信道估计方案。仿真结果表明，所提出的码本设计不仅以更低的泄漏效应实现了优越的近场信道稀疏化性能，还显著提高了压缩感知信道估计的精度。