发表机构
The Chinese University of Hong Kong; University of Electronic Science and Technology of China（香港中文大学; 电子科技大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出基于空间啁啾结构的可扩展框架，通过CSF模型和CHARM/E-CHARM算法，实现ELAA系统中近场多径信道参数的高精度联合估计，复杂度随阵列规模线性增长。
AI 中文摘要
本文提出了一种可扩展的框架，用于在超大规模天线阵列（ELAA）系统中进行高精度近场多径信道参数估计，能够从单次噪声观测中联合恢复路径数量、路径增益、角度和距离。关键思想是将近场多径信道解释为具有空间变化频率的空间啁啾分量的叠加，并通过分区ELAA架构利用这一结构。具体而言，我们建立了啁啾耦合子阵列远场（CSF）模型，其中每条近场路径在每个子阵列内被局部表示为具有恒定空间频率的远场正弦波，而这些局部空间频率通过由底层空间啁啾引起的线性关系在子阵列间耦合，形成特定于路径的啁啾轨迹。基于该模型，我们提出了啁啾耦合角度-距离估计（CHARM）算法，该算法执行无网格局部频率估计，随后进行跨子阵列轨迹恢复。为减轻CSF模型潜在的建模失配，我们进一步提出了增强型CHARM（E-CHARM）算法，该算法通过最大似然法在近场信道模型下细化CHARM估计。所提算法的计算复杂度随阵列规模线性增长。此外，仿真结果表明，所提算法实现了可靠的路径数量检测、高精度角度-距离估计和准确的信道重建。
英文摘要
This paper presents a scalable framework for high-precision near-field multipath channel parameter estimation in extremely large antenna array (ELAA) systems, enabling joint recovery of path number, path gains, angles, and ranges from a single noisy observation. The key idea is to interpret the near-field multipath channel as a superposition of spatial chirp components with spatially varying frequencies and exploit this structure through a partitioned ELAA architecture. Specifically, we establish a Chirp-coupled Subarray Far-field (CSF) model, where each near-field path is locally represented as a far-field sinusoid with a constant spatial frequency within each subarray, while these local spatial frequencies are coupled across subarrays through a linear relationship induced by the underlying spatial chirp, forming a path-specific chirp trajectory. Based on this model, we propose the CHirp-coupled Angular-Range estiMation (CHARM) algorithm, which performs gridless local frequency estimation followed by cross-subarray trajectory recovery. To mitigate the potential modeling mismatch of the CSF model, we further propose the enhanced CHARM (E-CHARM) algorithm, which refines the CHARM estimate under the near-field channel model through maximum likelihood. The computational complexity of the proposed algorithms scales linearly with the array size. Moreover, simulation results show that the proposed algorithms achieve reliable path-number detection, high-precision angle-range estimation, and accurate channel reconstruction.
