3D Channel Tracking for UAV-Satellite Communications in Space-Air-Ground Integrated Networks

• Published in: IEEE journal on selected areas in communications 2020-12, Vol.38 (12), p.2810-2823
• Main Authors: Yu, Jiadong, Liu, Xiaolan, Gao, Yue, Shen, Xuemin
• Format: Article
• Language: English
• Subjects: 5G mobile communication; Algorithms; Analytical models; Channel tracking; Communications systems; Correlation analysis; Logistics; Low earth orbits; Markov chains; massive antenna array; Mathematical model; Message passing; Optimization; Satellite communications; Satellite tracking; Space communications; Statistical analysis; Three dimensional models; Two dimensional models; UAV-satellite communication; Unmanned aerial vehicles; Wide area networks
• ISSN: 0733-8716; 1558-0008
• DOI: 10.1109/JSAC.2020.3005490

The space-air-ground integrated network (SAGIN) aims to provide seamless wide-area connections, high throughput and strong resilience for 5G and beyond communications. Acting as a crucial link segment of the SAGIN, unmanned aerial vehicle (UAV)-satellite communication has drawn much attention. However, it is a key challenge to track dynamic channel information due to the low earth orbit (LEO) satellite orbiting and three-dimensional (3D) UAV trajectory. In this paper, we explore the 3D channel tracking for a Ka-band UAV-satellite communication system. We firstly propose a statistical dynamic channel model called 3D two-dimensional Markov model (3D-2D-MM) for the UAV-satellite communication system by exploiting the probabilistic insight relationship of both hidden value vector and joint hidden support vector. Specifically, for the joint hidden support vector, we consider a more realistic 3D support vector in both azimuth and elevation direction. Moreover, the spatial sparsity structure and the time-varying probabilistic relationship between degree patterns named the spatial and temporal correlation, respectively, are studied for each direction. Furthermore, we derive a novel 3D dynamic turbo approximate message passing (3D-DTAMP) algorithm to recursively track the dynamic channel with the 3D-2D-MM priors. Numerical results show that our proposed algorithm achieves superior channel tracking performance to the state-of-the-art algorithms with lower pilot overhead and comparable complexity.