Orthogonal Time Frequency Space (OTFS) modulation offers robust performance in high-mobility scenarios by transforming time-varying channels into the delay-Doppler (DD) domain. However, in high-mobility environment such as emerging 5G Non-Terrestrial Networks (NTN), the extreme orbital velocities of Low Earth Orbit (LEO) satellites frequently cause the physical Doppler shifts to exceed the fundamental grid range. This Doppler ambiguity induces severe model mismatch and renders traditional MLE channel estimators ineffective. To address this challenge, this paper proposes a novel low-complexity pilot-aided Doppler ambiguity detection and compensation framework. We first mathematically derive the OTFS input-output relationship in the presence of aliasing, revealing that Doppler ambiguity manifests itself as a distinct phase rotation along the delay dimension. Leveraging this insight, we developed a two-stage estimator that utilizes pairwise phase differences between pilot symbols to identify the integer ambiguity, followed by a refined Maximum Likelihood Estimation (MLE) for channel recovery. We investigate two pilot arrangements, Embedded Pilot with Guard Zone (EP-GZ) and Data-Surrounded Pilot (DSP), to analyze the trade-off between interference suppression and spectral efficiency. Simulation results demonstrate that the proposed scheme effectively eliminates the error floor caused by ambiguity, achieving Bit Error Rate (BER) and Normalized Mean Square Error (NMSE) performance comparable to the exhaustive search benchmark while maintaining a computational complexity similar to standard MLE.

翻译：正交时频空间（OTFS）调制通过将时变信道转换至时延-多普勒（DD）域，在高移动性场景中提供了鲁棒的性能。然而，在诸如新兴的5G非地面网络（NTN）等高移动性环境中，低地球轨道（LEO）卫星的极端轨道速度常导致物理多普勒频移超出基本网格范围。这种多普勒模糊度会引发严重的模型失配，并使传统的最大似然估计（MLE）信道估计器失效。为应对这一挑战，本文提出了一种新颖的低复杂度导频辅助多普勒模糊度检测与补偿框架。我们首先从数学上推导了存在混叠情况下的OTFS输入-输出关系，揭示了多普勒模糊度表现为沿时延维度的独特相位旋转。基于这一洞察，我们开发了一种两阶段估计器：首先利用导频符号之间的成对相位差来识别整数模糊度，随后采用精细化的最大似然估计（MLE）进行信道恢复。我们研究了两种导频布置方案——带保护区的嵌入式导频（EP-GZ）和数据环绕导频（DSP），以分析干扰抑制与频谱效率之间的权衡。仿真结果表明，所提方案能有效消除由模糊度引起的错误平层，其误码率（BER）和归一化均方误差（NMSE）性能与穷举搜索基准相当，同时保持了与标准MLE相似的计算复杂度。