This paper investigates joint device identification, channel estimation, and signal detection for LEO satellite-enabled grant-free random access, where a multiple-input multipleoutput (MIMO) system with orthogonal time-frequency space modulation (OTFS) is utilized to combat the dynamics of the terrestrial-satellite link (TSL). We divide the receiver structure into three modules: first, a linear module for identifying active devices, which leverages the generalized approximate message passing (GAMP) algorithm to eliminate inter-user interference in the delay-Doppler domain; second, a non-linear module adopting the message passing algorithm to jointly estimate channel and detect transmit signals; the third aided by Markov random field (MRF) aims to explore the three dimensional block sparsity of channel in the delay-Doppler-angle domain. The soft information is exchanged iteratively between these three modules by careful scheduling. Furthermore, the expectation-maximization algorithm is embedded to learn the hyperparameters in prior distributions. Simulation results demonstrate that the proposed scheme outperforms the conventional methods significantly in terms of activity error rate, channel estimation accuracy, and symbol error rate.

翻译：本文研究了低轨卫星支持的无授权随机接入中的联合设备识别、信道估计与信号检测问题，其中采用正交时频空调制（OTFS）的多输入多输出（MIMO）系统来应对地星链路（TSL）的动态特性。我们将接收机结构划分为三个模块：第一，利用广义近似消息传递（GAMP）算法消除延迟-多普勒域中用户间干扰的线性模块，用于识别活跃设备；第二，采用消息传递算法联合估计信道与检测发送信号的非线性模块；第三，借助马尔可夫随机场（MRF）探索信道在延迟-多普勒-角度域中三维块稀疏性的辅助模块。通过精心调度，这三个模块之间迭代交换软信息。此外，还嵌入了期望最大化算法以学习先验分布中的超参数。仿真结果表明，所提方案在活跃度错误率、信道估计精度和符号错误率方面显著优于传统方法。