3-D Trajectory Optimization for Fixed-Wing UAV-Enabled Wireless Network
Unmanned aerial vehicles (UAVs) is a promising technology for the next-generation communication systems. In this article, a fixed-wing UAV is considered to enhance the connectivity for far-users at the coverage region of an overcrowded base station (BS). In particular, a three dimensions (3D) UAV tr...
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IEEE
2021-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9360597/ |
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| author | Alessandro Visintini Tharindu D. Ponnimbaduge Perera Dushantha Nalin K. Jayakody |
| author_facet | Alessandro Visintini Tharindu D. Ponnimbaduge Perera Dushantha Nalin K. Jayakody |
| author_sort | Alessandro Visintini |
| collection | DOAJ |
| description | Unmanned aerial vehicles (UAVs) is a promising technology for the next-generation communication systems. In this article, a fixed-wing UAV is considered to enhance the connectivity for far-users at the coverage region of an overcrowded base station (BS). In particular, a three dimensions (3D) UAV trajectory is optimized to improve the overall energy efficiency of the communication system by considering the system throughput and the UAV’s energy consumption for a given finite time horizon. The solutions for the proposed optimization problem are derived by applying Lagrangian optimization and using an algorithm based on successive convex iteration techniques. Numerical results demonstrate that by optimizing the UAV’s trajectory in the 3D space, the proposed system design achieves significantly higher energy efficiency with the gain reaching up to <inline-formula> <tex-math notation="LaTeX">$20\,\,bitsJ^{-1}$ </tex-math></inline-formula> compared to the <inline-formula> <tex-math notation="LaTeX">$14\,\,bitsJ^{-1}$ </tex-math></inline-formula> maximum gain achieved by the 2D space trajectory. Further, results reveal that the proposed algorithm converge earlier in 3D space trajectory compare to the 2D space trajectory. |
| format | Article |
| id | doaj-art-098be5fd3cf94e749c8219a4276a1acd |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-098be5fd3cf94e749c8219a4276a1acd2024-12-11T00:02:15ZengIEEEIEEE Access2169-35362021-01-019350453505610.1109/ACCESS.2021.306116393605973-D Trajectory Optimization for Fixed-Wing UAV-Enabled Wireless NetworkAlessandro Visintini0https://orcid.org/0000-0001-5632-8513Tharindu D. Ponnimbaduge Perera1https://orcid.org/0000-0002-2802-8086Dushantha Nalin K. Jayakody2https://orcid.org/0000-0002-7004-2930Industrial Engineering, Politecnico Di Milano, Milan, ItalySchool of Computer Science and Robotics, National Research Tomsk Polytechnic University, Tomsk, RussiaSchool of Computer Science and Robotics, National Research Tomsk Polytechnic University, Tomsk, RussiaUnmanned aerial vehicles (UAVs) is a promising technology for the next-generation communication systems. In this article, a fixed-wing UAV is considered to enhance the connectivity for far-users at the coverage region of an overcrowded base station (BS). In particular, a three dimensions (3D) UAV trajectory is optimized to improve the overall energy efficiency of the communication system by considering the system throughput and the UAV’s energy consumption for a given finite time horizon. The solutions for the proposed optimization problem are derived by applying Lagrangian optimization and using an algorithm based on successive convex iteration techniques. Numerical results demonstrate that by optimizing the UAV’s trajectory in the 3D space, the proposed system design achieves significantly higher energy efficiency with the gain reaching up to <inline-formula> <tex-math notation="LaTeX">$20\,\,bitsJ^{-1}$ </tex-math></inline-formula> compared to the <inline-formula> <tex-math notation="LaTeX">$14\,\,bitsJ^{-1}$ </tex-math></inline-formula> maximum gain achieved by the 2D space trajectory. Further, results reveal that the proposed algorithm converge earlier in 3D space trajectory compare to the 2D space trajectory.https://ieeexplore.ieee.org/document/9360597/Energy efficiencysequential convex optimizationtrajectory optimizationUAV communication5G |
| spellingShingle | Alessandro Visintini Tharindu D. Ponnimbaduge Perera Dushantha Nalin K. Jayakody 3-D Trajectory Optimization for Fixed-Wing UAV-Enabled Wireless Network IEEE Access Energy efficiency sequential convex optimization trajectory optimization UAV communication 5G |
| title | 3-D Trajectory Optimization for Fixed-Wing UAV-Enabled Wireless Network |
| title_full | 3-D Trajectory Optimization for Fixed-Wing UAV-Enabled Wireless Network |
| title_fullStr | 3-D Trajectory Optimization for Fixed-Wing UAV-Enabled Wireless Network |
| title_full_unstemmed | 3-D Trajectory Optimization for Fixed-Wing UAV-Enabled Wireless Network |
| title_short | 3-D Trajectory Optimization for Fixed-Wing UAV-Enabled Wireless Network |
| title_sort | 3 d trajectory optimization for fixed wing uav enabled wireless network |
| topic | Energy efficiency sequential convex optimization trajectory optimization UAV communication 5G |
| url | https://ieeexplore.ieee.org/document/9360597/ |
| work_keys_str_mv | AT alessandrovisintini 3dtrajectoryoptimizationforfixedwinguavenabledwirelessnetwork AT tharindudponnimbadugeperera 3dtrajectoryoptimizationforfixedwinguavenabledwirelessnetwork AT dushanthanalinkjayakody 3dtrajectoryoptimizationforfixedwinguavenabledwirelessnetwork |