TY - GEN
T1 - Energy harvesting in unmanned aerial vehicle networks with 3d antenna radiation patterns
AU - Turgut, Esma
AU - Gursoy, M. Cenk
AU - Guvenc, Ismail
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/9
Y1 - 2019/9
N2 - In this paper, an analytical framework is provided to analyze the energy coverage performance of unmanned aerial vehicle (UAV) energy harvesting networks with clustered user equipments (UEs). Locations of UAVs are modeled as a Poison Point Process (PPP), while locations of UEs are modeled as a Poisson Cluster Process (PCP). Two different models are considered for the line-of-sight (LOS) probability function to compare their effect on the network performance. Moreover, ultra-wideband (UWB) antennas with doughnut-shaped radiation patterns are employed in both UAVs and UEs, and the impact of practical 3D antenna radiation patterns on the network performance is also investigated. Initially, the complementary cumulative distribution function (CCDF) and probability density function (PDF) of path losses for each tier are derived. Subsequently, association probabilities with each tier are obtained. Energy coverage probability is derived for the entire network using tools from stochastic geometry. Via numerical results, we show that UAV height and antenna orientation play crucial roles on the energy coverage performance.
AB - In this paper, an analytical framework is provided to analyze the energy coverage performance of unmanned aerial vehicle (UAV) energy harvesting networks with clustered user equipments (UEs). Locations of UAVs are modeled as a Poison Point Process (PPP), while locations of UEs are modeled as a Poisson Cluster Process (PCP). Two different models are considered for the line-of-sight (LOS) probability function to compare their effect on the network performance. Moreover, ultra-wideband (UWB) antennas with doughnut-shaped radiation patterns are employed in both UAVs and UEs, and the impact of practical 3D antenna radiation patterns on the network performance is also investigated. Initially, the complementary cumulative distribution function (CCDF) and probability density function (PDF) of path losses for each tier are derived. Subsequently, association probabilities with each tier are obtained. Energy coverage probability is derived for the entire network using tools from stochastic geometry. Via numerical results, we show that UAV height and antenna orientation play crucial roles on the energy coverage performance.
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U2 - 10.1109/VTCFall.2019.8891520
DO - 10.1109/VTCFall.2019.8891520
M3 - Conference contribution
AN - SCOPUS:85075260215
T3 - IEEE Vehicular Technology Conference
BT - 2019 IEEE 90th Vehicular Technology Conference, VTC 2019 Fall - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 90th IEEE Vehicular Technology Conference, VTC 2019 Fall
Y2 - 22 September 2019 through 25 September 2019
ER -