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DC Field | Value | Language |
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dc.contributor.author | Gupta, N. | - |
dc.contributor.author | Mishra, D. | - |
dc.contributor.author | Agrawal, S. | - |
dc.date.accessioned | 2022-07-10T16:28:27Z | - |
dc.date.available | 2022-07-10T16:28:27Z | - |
dc.date.issued | 2022-07-10 | - |
dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/3606 | - |
dc.description.abstract | This paper studies the flight trajectory of unmanned aerial vehicles (UAV) to provide fifth-generation (5G) cellular service in a given area. We consider a single UAV launched from the fixed initial to the final location, during which it serves the ground users that are distributed in a circular field. UAV’s limited on-board energy has been a major concern affecting the system’s performance. Therefore, in this work, we minimize the average outage probability of the system by optimizing the three-dimensional (3D) trajectory of the UAV while considering the velocity and on-board energy as constraints. To solve this problem, we propose two approaches: the low-complexity vertex and the high-performance sequential approach. The vertex approach involves two steps. Firstly, it obtains the optimal solution while relaxing the velocity and on-board energy constraints. Secondly, a greedy solution is proposed for the original problem. The sequential approach finds the optimal location in each time slot sequentially. Simulation results compare the two approaches and show that our proposed strategies provide on an average 41% improvement in average outage probability over the benchmark schemes. Additionally, we show that the sequential approach is better than the vertex approach, though at the cost of high computational complexity. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | UAV communication | en_US |
dc.subject | outage probability | en_US |
dc.subject | trajectory optimization | en_US |
dc.subject | on-board energy constraint | en_US |
dc.title | Energy-Aware Trajectory Design for Outage Minimization in UAV-Assisted Communication Systems | en_US |
dc.type | Article | en_US |
Appears in Collections: | Year-2022 |
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File | Description | Size | Format | |
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Full Text.pdf | 3.32 MB | Adobe PDF | View/Open Request a copy |
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