Low Earth orbit (LEO) satellite systems experience significant Doppler effects due to high mobility. While Doppler shifts can be largely compensated, residual frequency uncertainty induces a structured form of channel uncertainty that can limit achievable rates. We model this effect using a block-fading channel of the form $ \mathbf{H} = \mathbf{F} + s \mathbf{G} $, where $s$ is an unknown scalar random parameter. We first study this model in a general $N\times N$ MIMO setting. For this channel, we derive achievable rate lower bounds based on explicit transmission schemes and capacity upper bounds using a duality approach. We study Gaussian signaling and propose a practical superposition scheme with subspace alignment (SN) and successive interference cancellation, where a coarse-layer stream serves as an implicit pilot for decoding refined-layer data. We characterize asymptotic capacity in the near-coherent and high-SNR regimes, and show via Doppler-OFDM simulations that the proposed SN scheme achieves near-optimal rates with low complexity.

翻译：低地球轨道（LEO）卫星系统因高速运动而经历显著的多普勒效应。虽然多普勒频移可被大幅补偿，但残余频率不确定性会引入一种结构化的信道不确定性，从而限制可达速率。我们使用形式为 $ \mathbf{H} = \mathbf{F} + s \mathbf{G} $ 的块衰落信道对此效应进行建模，其中 $s$ 是一个未知的标量随机参数。我们首先在一般的 $N\times N$ MIMO 场景下研究该模型。针对此信道，我们基于显式传输方案推导了可达速率下界，并利用对偶方法推导了容量上界。我们研究了高斯信令，并提出了一种具有子空间对齐（SN）和连续干扰消除的实用叠加方案，其中粗层数据流作为解码细层数据的隐式导频。我们刻画了近相干和高信噪比（SNR）区域的渐近容量，并通过多普勒-OFDM 仿真表明，所提出的 SN 方案能以低复杂度实现接近最优的速率。