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arXiv 2603.09293cs.ITmath.IT
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基于张量列车分解的MIMO-AFDM系统信道估计

Tensor Train Decomposition-based Channel Estimation for MIMO-AFDM Systems with Fractional Delay and Doppler

National Mobile Communications Research Laboratory, Southeast University(东南大学)

Ruizhe Wang, Cunhua Pan, Hong Ren, Haisu Wu, Jiangzhou Wang

AI总结:

本文提出基于时间-频率域导频结构的张量列车分解算法,用于改进MIMO-AFDM系统中分数延迟和多普勒频率估计的精度与效率。

摘要:

仿射频率分割(AFDM)作为一种基于啁啾的多载波技术,已展现出在高速通信系统中的巨大潜力。为了充分利用AFDM提供的分集增益,精确的信道估计至关重要。然而,现有研究主要集中在整数延迟Tap场景和单符号导频估计。由于实际中的延迟Tap通常是分数的,将其近似为整数不仅会降低延迟估计精度,还会严重影响多普勒频率估计。为了解决这个问题,本文研究了多输入多输出(MIMO)-AFDM系统的信道估计。提出了一种时间-仿射频率(T-AF)域导频结构,以利用时域相位变化。通过利用空间和时域中的旋转不变性特性,开发了一种基于Vandermonde结构张量列车(TT)分解的信道估计算法。所提出的算法在计算效率方面优于现有参数估计方法。此外,与现有研究不同,本文推导了全局Ziv-Zakai界(ZZB)作为Cramér-Rao界(CRB)的替代参数估计误差下界。数值结果表明,推导出的ZZB提供了更紧的全局性能表征,并成功捕捉了低信噪比(SNR)情况下均方误差(MSE)性能的阈值现象。此外,所提出的算法在通信性能上优于现有方案,同时提供计算速度提升,将执行时间减少了一个数量级,相比现有迭代算法。

英文摘要:

Affine Frequency Division Multiplexing (AFDM) has emerged as a promising chirp-based multicarrier technology for high-speed communication systems. To fully exploit the diversity gain offered by AFDM, accurate channel estimation is essential. However, existing studies have mainly focused on the integer-delay-tap scenario and single-symbol pilot-based estimation. Since delay taps in practice are generally fractional, approximating them as integers not only degrades delay estimation accuracy but also severely affects Doppler frequency estimation. To address this problem, in this paper, we investigate channel estimation for multiple-input multiple-output (MIMO)-AFDM systems. A time-affine frequency (T-AF) domain pilot structure is proposed to exploit time-domain phase variations. By leveraging the rotational invariance property in the spatial and temporal domains, a channel estimation algorithm based on Vandermonde-structured tensor-train (TT) decomposition is developed. The proposed algorithm demonstrates superior computational efficiency compared with state-of-the-art parameter estimation methods. Moreover, diverging from current studies, we derive the global Ziv-Zakai bound (ZZB) as an alternative parameter estimation error lower bound to the Cramér-Rao bound (CRB). Numerical results show that the derived ZZB provides tighter global performance characterization and successfully captures the threshold phenomenon in mean square error (MSE) performance in the low-SNR regime. Furthermore, the proposed algorithm achieves superior communication performance relative to the existing schemes, while offering a computational speedup, reducing the execution time by an order of magnitude compared to the state-of-the-art iterative algorithms.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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