User Activity Detection and Channel Estimation for Grant-Free Random Access in LEO Satellite-Enabled Internet of Things
User Activity Detection and Channel Estimation for Grant-Free Random Access in LEO Satellite-Enabled Internet of Things
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DOI：
10.1109/jiot.2020.2997336
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发表时间：
2020-05
影响因子：
10.6
通讯作者：
Zhaoji Zhang;Ying Li;Chongwen Huang;Qinghua Guo;Lei Liu;C. Yuen;Y. Guan
中科院分区：
文献类型：
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作者：
Zhaoji Zhang;Ying Li;Chongwen Huang;Qinghua Guo;Lei Liu;C. Yuen;Y. Guan
随着密集低地球轨道（LEO）星座的最新进展，LEO卫星网络已成为为物联网（IoT）服务提供全球覆盖的一种有前途的解决方案。针对随机激活的物联网设备的零星传输，考虑随机接入机制，提出了一种免授权接入（GF-RA）方案，以降低移动的LEO卫星的接入时延。提出了一种基于期望最大化的Bernoulli-Rician消息传递（BR-MP-EM）算法，用于解决地面-卫星GF-RA系统中的用户活动检测（UAD）和信道估计（CE）问题。该BR-MP-EM算法分为两个阶段。在内部迭代中，Bernoulli消息和Rician消息被更新用于联合UAD和CE问题。基于内迭代的输出，在外迭代中采用期望最大化（EM）方法来更新与信道损伤相关的超参数。最后，仿真结果表明，所提出的BR-MP-EM算法的UAD和CE的准确性，以及对信道损伤的鲁棒性。
With recent advances on the dense low-Earth orbit (LEO) constellation, the LEO satellite network has become one promising solution for 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 hyperparameters 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.