Tri Nhu Do, Georges Kaddoum, Thanh Luan Nguyen, Daniel Benevides da Costa, and Zygmunt J. Haas
IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2021
In this paper, we propose and investigate an aerial reconfigurable intelligent surface (aerial-RIS)-aided wireless com- munication system. Specifically, considering practical composite fading channels, we characterize the air-to-ground (A2G) links by Namkagami-m small-scale fading and inverse-Gamma large- scale shadowing. To investigate the delay-limited performance of the proposed system, we derive a tight approximate closed- form expression for the end-to-end outage probability (OP). Next, considering a mobile environment, where performance analysis is intractable, we rely on machine learning-based performance prediction to evaluate the performance of the mobile aerial- RIS-aided system. Specifically, taking into account the three- dimensional (3D) spatial movement of the aerial-RIS, we build a deep neural network (DNN) to accurately predict the OP. We show that: (i) fading and shadowing conditions have strong impact on the OP, (ii) as the number of reflecting elements increases, aerial-RIS achieves higher energy efficiency (EE), and (iii) the aerial-RIS-aided system outperforms conventional relaying systems.
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@INPROCEEDINGS{DoPIMRC2021,
author={Do, Tri Nhu and Kaddoum, Georges and Nguyen, Thanh Luan and da Costa, Daniel Benevides and Haas, Zygmunt J.},
booktitle={2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)},
title={Aerial Reconfigurable Intelligent Surface-Aided Wireless Communication Systems},
year={2021},
pages={525-530},
address={Helsinki, Finland},
doi={10.1109/PIMRC50174.2021.9569450}}