Lower earth orbit (LEO) satellites play an important role in the integration of space and terrestrial communication networks, which typically encounter high-mobility scenarios. It has been shown that orthogonal time frequency space (OTFS) modulation performs well in such high-mobility scenarios by transforming the time-varying channels into the delay-Doppler domain. In this paper, we develop a joint channel estimation and data detection algorithm for OTFS-based LEO satellite communications. Firstly, we adopt the powerful variational Bayesian inference (VBI) method for estimating the delay-Doppler channel vector, which contains the channel gain, the delay and the Doppler. Secondly, we exploit the unknown data symbols in an OTFS frame as ‘virtual pilots’ for improving the accuracy of channel estimation and detect them simultaneously. Our simulation results demonstrate that the proposed algorithm achieves improved channel estimation mean square error and bit error rate performance than its conventional counterparts.

中文翻译：

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LEO 卫星通信中 OTFS 系统的联合贝叶斯信道估计和数据检测


低地球轨道（LEO）卫星在空间和地面通信网络的融合中发挥着重要作用，通常会遇到高移动性场景。事实证明，正交时频空间（OTFS）调制通过将时变信道变换到延迟多普勒域，在这种高移动性场景中表现良好。在本文中，我们为基于 OTFS 的 LEO 卫星通信开发了一种联合信道估计和数据检测算法。首先，我们采用强大的变分贝叶斯推理（VBI）方法来估计延迟多普勒信道向量，其中包含信道增益、延迟和多普勒。其次，我们利用 OTFS 帧中的未知数据符号作为“虚拟导频”，以提高信道估计的准确性并同时检测它们。我们的仿真结果表明，与传统算法相比，所提出的算法实现了改进的信道估计均方误差和误码率性能。