Quasi-Synchronous Random Access for Massive MIMO-Based LEO Satellite Constellations

Keke Ying, Zhen Gao*, Sheng Chen, Mingyu Zhou, Dezhi Zheng, Symeon Chatzinotas, Bjorn Ottersten, H. Vincent Poor

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

15 引用 (Scopus)

摘要

Low earth orbit (LEO) satellite constellation-enabled communication networks are expected to be an important part of many Internet of Things (IoT) deployments due to their unique advantage of providing seamless global coverage. In this paper, we investigate the random access problem in massive multiple-input multiple-output-based LEO satellite systems, where the multi-satellite cooperative processing mechanism is considered. Specifically, at edge satellite nodes, we conceive a training sequence padded multi-carrier system to overcome the issue of imperfect synchronization, where the training sequence is utilized to detect the devices' activity and estimate their channels. Considering the inherent sparsity of terrestrial-satellite links and the sporadic traffic feature of IoT terminals, we utilize the orthogonal approximate message passing-multiple measurement vector algorithm to estimate the delay coefficients and user terminal activity. To further utilize the structure of the receive array, a two-dimensional estimation of signal parameters via rotational invariance technique is performed for enhancing channel estimation. Finally, at the central server node, we propose a majority voting scheme to enhance activity detection by aggregating backhaul information from multiple satellites. Moreover, multi-satellite cooperative linear data detection and multi-satellite cooperative Bayesian dequantization data detection are proposed to cope with perfect and quantized backhaul, respectively. Simulation results verify the effectiveness of our proposed schemes in terms of channel estimation, activity detection, and data detection for quasi-synchronous random access in satellite systems.

源语言英语
页(从-至)1702-1722
页数21
期刊IEEE Journal on Selected Areas in Communications
41
6
DOI
出版状态已出版 - 1 6月 2023

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