The meta distribution of SINR in UAV-assisted cellular networks
Mounting compact and lightweight base stations on unmanned aerial vehicles (UAVs) is a cost-effective and flexible solution to provide seamless coverage on the existing terrestrial networks. While the coverage probability in UAV-assisted cellular networks has been widely investigated, it provides on...
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sg-ntu-dr.10356-1720722023-11-21T05:09:50Z The meta distribution of SINR in UAV-assisted cellular networks Shi, Minwei Yang, Kai Niyato, Dusit Yuan, Hang Zhou, He Xu, Zhan School of Computer Science and Engineering Engineering::Computer science and engineering Unmanned Aerial Vehicles Terrestrial Networks Mounting compact and lightweight base stations on unmanned aerial vehicles (UAVs) is a cost-effective and flexible solution to provide seamless coverage on the existing terrestrial networks. While the coverage probability in UAV-assisted cellular networks has been widely investigated, it provides only the first-order statistic of signal-to-interference-plus-noise ratio (SINR). In this paper, to analyze high-order statistics of SINR and characterize the disparity among individual links, we provide a meta distribution (MD)-based analytical framework for UAV-assisted cellular networks, in which the probabilistic line-of-sight channel and realistic antenna pattern are taken into account for air-to-ground transmissions. To accurately characterize the interference from UAVs, we relax the widely applied uniform off-boresight angle (OBA) assumption and derive the exact distribution of OBA. Using stochastic geometry, for both steerable and vertical antenna scenarios, we obtain mathematical expressions for the moments of condition success probability, the SINR MD, and the mean local delay. Moreover, we study the asymptotic behavior of the moments as network density approaches infinity. Numerical results validate the tightness of the theoretical results and show that the uniform OBA assumption underestimates the network performance, especially in the regime of moderate altitude of UAV. We also show that when UAVs are equipped with steerable antennas, the network coverage and user fairness can be optimized simultaneously by carefully adjusting the UAV parameters. Info-communications Media Development Authority (IMDA) National Research Foundation (NRF) This work was supported in part by the National Key Research and Development Program of China under Grant 2022YFC3301200; in part by the National Natural Science Foundation of China under Grant 62201055; in part by the National Research Foundation (NRF), Singapore and Infocomm Media Development Authority under the Future Communications Research Development Programme (FCP), and DSO National Laboratories under the AI Singapore Programme (AISG Award No: AISG2-RP-2020-019). 2023-11-21T05:09:50Z 2023-11-21T05:09:50Z 2023 Journal Article Shi, M., Yang, K., Niyato, D., Yuan, H., Zhou, H. & Xu, Z. (2023). The meta distribution of SINR in UAV-assisted cellular networks. IEEE Transactions On Communications, 71(2), 1193-1206. https://dx.doi.org/10.1109/TCOMM.2022.3233064 0090-6778 https://hdl.handle.net/10356/172072 10.1109/TCOMM.2022.3233064 2-s2.0-85146237775 2 71 1193 1206 en AISG2-RP-2020-019 IEEE Transactions on Communications © 2022 IEEE. All rights reserved. |
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Engineering::Computer science and engineering Unmanned Aerial Vehicles Terrestrial Networks Shi, Minwei Yang, Kai Niyato, Dusit Yuan, Hang Zhou, He Xu, Zhan The meta distribution of SINR in UAV-assisted cellular networks |
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Mounting compact and lightweight base stations on unmanned aerial vehicles (UAVs) is a cost-effective and flexible solution to provide seamless coverage on the existing terrestrial networks. While the coverage probability in UAV-assisted cellular networks has been widely investigated, it provides only the first-order statistic of signal-to-interference-plus-noise ratio (SINR). In this paper, to analyze high-order statistics of SINR and characterize the disparity among individual links, we provide a meta distribution (MD)-based analytical framework for UAV-assisted cellular networks, in which the probabilistic line-of-sight channel and realistic antenna pattern are taken into account for air-to-ground transmissions. To accurately characterize the interference from UAVs, we relax the widely applied uniform off-boresight angle (OBA) assumption and derive the exact distribution of OBA. Using stochastic geometry, for both steerable and vertical antenna scenarios, we obtain mathematical expressions for the moments of condition success probability, the SINR MD, and the mean local delay. Moreover, we study the asymptotic behavior of the moments as network density approaches infinity. Numerical results validate the tightness of the theoretical results and show that the uniform OBA assumption underestimates the network performance, especially in the regime of moderate altitude of UAV. We also show that when UAVs are equipped with steerable antennas, the network coverage and user fairness can be optimized simultaneously by carefully adjusting the UAV parameters. |
author2 |
School of Computer Science and Engineering |
author_facet |
School of Computer Science and Engineering Shi, Minwei Yang, Kai Niyato, Dusit Yuan, Hang Zhou, He Xu, Zhan |
format |
Article |
author |
Shi, Minwei Yang, Kai Niyato, Dusit Yuan, Hang Zhou, He Xu, Zhan |
author_sort |
Shi, Minwei |
title |
The meta distribution of SINR in UAV-assisted cellular networks |
title_short |
The meta distribution of SINR in UAV-assisted cellular networks |
title_full |
The meta distribution of SINR in UAV-assisted cellular networks |
title_fullStr |
The meta distribution of SINR in UAV-assisted cellular networks |
title_full_unstemmed |
The meta distribution of SINR in UAV-assisted cellular networks |
title_sort |
meta distribution of sinr in uav-assisted cellular networks |
publishDate |
2023 |
url |
https://hdl.handle.net/10356/172072 |
_version_ |
1783955598227800064 |