Beamforming Design and Performance Analysis for Satellite and UAV Integrated Networks in IoRT Applications

Abstract
Satellite and unmanned aerial vehicles (UAV) integrated networks (SUINs) are considered as a promising method to offer various internet of remote things (IoRT) applications. In this paper, we investigate the downlink transmission of SUINs where the satellite to UAV link uses free-space optical (FSO) technology with equal gain combining (EGC) scheme while the links from UAV to IoRT devices exploit radio frequency (RF) with space division multiple access (SDMA) technique. Specifically, considering that only statistical channel state information (CSI) is available, we first formulate an optimization problem to maximize the ergodic sum rate (ESR) of the system, which is constrained by total transmit power budget and IoRT devices’ rate requirements. Then, a beamforming (BF) scheme based on alternating direction method of multipliers (ADMM) is proposed to solve the non-convex problem. Furthermore, a zero-forcing (ZF) based suboptimal approach is also presented to reduce the implementation complexity. Finally, by assuming that the FSO link and RF links are subject to Gamma-Gamma fading and Nakagami-m fading, respectively, we derive closed-form ESR expressions for the considered network with the proposed BF schemes. Simulation results are provided to confirm the accuracy of theoretical analysis. Moreover, it is revealed that our proposed EGC scheme for FSO communication and BF schemes for RF transmission can both achieve better performance than the existing works.

Citation
Kong, H., Lin, M., Zhang, J., Ouyang, J., Zhu, W.-P., & Alouini, M.-S. (2022). Beamforming Design and Performance Analysis for Satellite and UAV Integrated Networks in IoRT Applications. IEEE Internet of Things Journal, 1–1. https://doi.org/10.1109/jiot.2022.3170429

Acknowledgements
Supported by the Key International Cooperation Research Project under Grant 61720106003

Publisher
Institute of Electrical and Electronics Engineers (IEEE)

Journal
IEEE Internet of Things Journal

DOI
10.1109/jiot.2022.3170429

Additional Links
https://ieeexplore.ieee.org/document/9766223/

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