基于张量分解的XL-MIMO AFDM系统混合场感知
Tensor Decomposition Based Mixed-Field Sensing for XL-MIMO AFDM Systems
- Shanghai Jiao Tong University（上海交通大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文针对XL-MIMO AFDM系统近场耦合与动态散射挑战，提出基于张量分解的混合场感知方案，实现参数解耦与连续域估计，显著提升时延-多普勒精度并消除角度误差地板。
AI中文摘要：
由超大规模MIMO（XL-MIMO）和仿射频分复用（AFDM）赋能的集成感知与通信是车载网络中极具前景的范式。然而，近场球面波前畸变导致严重的非线性参数耦合，而高度动态的散射环境加剧了失配误差。为应对这些关键挑战，本文提出了一种新颖的基于张量的感知方案，用于XL-MIMO AFDM系统。首先，将接收信号重构为张量，随后利用因子矩阵固有的Vandermonde结构，采用高效的分解方法。这使得参数可以直接从分解后的矩阵中估计，有效避免了参数间耦合。接着，提出了一种对称解耦和实域流形优化算法用于到达角估计，规避了近场效应通常导致的高维搜索。此外，开发了一种基带重构和解析梯度算法，在连续参数域中执行时延-多普勒估计，从根本上消除了高机动场景中固有的网格失配误差。利用这些解耦因子，剩余的未知离开角可以轻松提取。大量仿真结果表明，所提方案在时延-多普勒精度上实现了数量级的提升，并消除了严重制约最先进基线的角度估计误差地板。
英文摘要：
Integrated sensing and communications enabled by extremely large-scale MIMO (XL-MIMO) and affine frequency division multiplexing (AFDM) is a highly promising paradigm for vehicular networks. However, the near-field spherical wavefront distortions induce severe non-linear parameter coupling, while the highly dynamic scattering environments exacerbate mismatch errors. To address these critical challenges, this paper proposes a novel tensor-based sensing scheme for XL-MIMO AFDM systems. First, the received signals are reformulated into a tensor, followed by an efficient decomposition approach that exploits the inherent Vandermonde structure of the factor matrices. This allows parameters to be directly estimated from the decomposed matrices, effectively avoiding inter-parameter coupling. Subsequently, a symmetric decoupling and real-domain manifold optimization algorithm is proposed for angle of arrival estimation, circumventing the high-dimensional searches typically induced by near-field effects. Furthermore, a baseband reconstruction and analytical gradient-based algorithm is developed to perform delay-Doppler estimation in the continuous parameter domain, fundamentally eradicating the grid-mismatch errors inherent in high-mobility scenarios. With these decoupled factors, the remaining unknown angle of departure can be readily extracted. Extensive simulation results demonstrate that the proposed scheme achieves orders-of-magnitude improvements in delay-Doppler accuracy and eliminates the error floors in angular estimation that severely bottleneck state-of-the-art baselines.
