In this paper, we propose a novel cross-domain channel estimation (CDCE) algorithm for orthogonal frequency division multiplexing (OFDM) systems, leveraging the unique characteristics of the delay-Doppler (DD) domain channel. Specifically, the proposed algorithm transforms the time-frequency (TF) domain pilot sequence of OFDM into the DD domain and applies a two-dimensional (2D) twisted-convolution for acquiring a coarse estimation of the underlying channel delay and Doppler. Then, the OFDM channel estimation is formulated as a sparse signal recovery problem in the TF domain according to the dictionary derived based on the obtained delay and Doppler estimates. Furthermore, a low-complexity $\ell_1$-regularized least-square estimator is proposed to effectively solve this problem. Moreover, we further develop a performance analysis framework of the proposed scheme based on the ambiguity function (AF) of the adopted pilot sequence. Our numerical results demonstrate noticeable estimation performance improvement compared to conventional OFDM channel estimation methods, particularly in the presence of high channel mobility.

翻译：本文针对正交频分复用（OFDM）系统，提出一种新颖的跨域信道估计（CDCE）算法，该算法利用了时延-多普勒（DD）域信道的独特特性。具体而言，所提算法将OFDM的时频（TF）域导频序列转换至DD域，并应用二维（2D）扭曲卷积以获取底层信道时延与多普勒的粗估计。随后，根据基于所得时延与多普勒估计推导出的字典，将OFDM信道估计建模为TF域中的稀疏信号恢复问题。此外，本文提出一种低复杂度的$\ell_1$正则化最小二乘估计器以有效求解该问题。进一步地，我们基于所采用导频序列的模糊函数（AF）建立了所提方案的性能分析框架。数值结果表明，相较于传统OFDM信道估计方法，所提方案在估计性能上取得了显著提升，尤其在信道高速移动场景下表现优异。