论文标题
用户活动检测和频道估计在利奥卫星启用的无授予随机访问中
User Activity Detection and Channel Estimation for Grant-Free Random Access in LEO Satellite-Enabled Internet-of-Things
论文作者
论文摘要
随着密集的低地球轨道（LEO）星座的最新进展，LEO卫星网络已成为为全球提供全球覆盖（IoT）服务的有希望的解决方案。面对来自随机激活的物联网设备的零星传输，我们考虑了随机访问（RA）机制，并提出了一种无资助的RA（GF-RA）方案，以减少对移动LEO卫星的访问延迟。对于此陆地 - 卫星GF-RA系统，提出了带有期望最大化（BR-MP-EM）算法的Bernoulli-Mrician消息，以解决用户活动检测（UAD）和通道估计（CE）问题。该BR-MP-EM算法分为两个阶段。在内部迭代中，对于联合UAD和CE问题，更新了Bernoulli消息和RICIAN消息。基于内部迭代的输出，在外迭代中采用了期望最大化（EM）方法来更新与通道障碍有关的超参数。最后，仿真结果表明所提出的BR-MP-EM算法的UAD和CE准确性以及针对通道障碍的鲁棒性。
With recent advances on the dense low-earth orbit (LEO) constellation, LEO satellite network has become one promising solution to providing global coverage for Internet-of-Things (IoT) services. Confronted with the sporadic transmission from randomly activated IoT devices, we consider the random access (RA) mechanism, and propose a grant-free RA (GF-RA) scheme to reduce the access delay to the mobile LEO satellites. A Bernoulli-Rician message passing with expectation maximization (BR-MP-EM) algorithm is proposed for this terrestrial-satellite GF-RA system to address the user activity detection (UAD) and channel estimation (CE) problem. This BR-MP-EM algorithm is divided into two stages. In the inner iterations, the Bernoulli messages and Rician messages are updated for the joint UAD and CE problem. Based on the output of the inner iterations, the expectation maximization (EM) method is employed in the outer iterations to update the hyper-parameters related to the channel impairments. Finally, simulation results show the UAD and CE accuracy of the proposed BR-MP-EM algorithm, as well as the robustness against the channel impairments.
