Trajectory Optimization for Cellular-Enabled UAV With Connectivity Outage Constraint

This paper studies the trajectory optimization problem of a single cellular-enabled unmanned aerial vehicle (UAV), taking into account the outage performance of the entire trajectory. To provide real-time control, it is critical for UAV to maintain reliable connectivity with the ground base station...

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Main Authors: Yu-Jia Chen, Da-Yu Huang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8984324/
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spelling doaj-8c8fddc76a8a447a86d5de875d9d0f892021-03-30T02:09:59ZengIEEEIEEE Access2169-35362020-01-018292052921810.1109/ACCESS.2020.29717728984324Trajectory Optimization for Cellular-Enabled UAV With Connectivity Outage ConstraintYu-Jia Chen0https://orcid.org/0000-0001-7563-4073Da-Yu Huang1https://orcid.org/0000-0003-1275-3512Department of Communication Engineering, National Central University, Taoyuan City, TaiwanDepartment of Communication Engineering, National Central University, Taoyuan City, TaiwanThis paper studies the trajectory optimization problem of a single cellular-enabled unmanned aerial vehicle (UAV), taking into account the outage performance of the entire trajectory. To provide real-time control, it is critical for UAV to maintain reliable connectivity with the ground base station (GBS). We first consider the connectivity outage performance, which is defined as the sum of the time duration of the outage performance not meeting a predefined threshold during the entire UAV mission. Then we formulate a trajectory optimization problem to minimize the mission completion time, while ensuring a sum constraint of the connectivity outage performance. We show that the connectivity outage constraint can be transformed into a flying area constraint. Since the formulated problem is NP-hard, a low-complexity method is proposed to solve the problem by finding the shortest path in an undirected weighted graph with enlarged GBS coverage. Simulation results demonstrate the superiority of the proposed scheme over other state-of-the-art schemes, in terms of trajectory length and computational complexity.https://ieeexplore.ieee.org/document/8984324/Unmanned aerial vehicle (UAV)trajectory optimizationcellular networks
collection DOAJ
language English
format Article
sources DOAJ
author Yu-Jia Chen
Da-Yu Huang
spellingShingle Yu-Jia Chen
Da-Yu Huang
Trajectory Optimization for Cellular-Enabled UAV With Connectivity Outage Constraint
IEEE Access
Unmanned aerial vehicle (UAV)
trajectory optimization
cellular networks
author_facet Yu-Jia Chen
Da-Yu Huang
author_sort Yu-Jia Chen
title Trajectory Optimization for Cellular-Enabled UAV With Connectivity Outage Constraint
title_short Trajectory Optimization for Cellular-Enabled UAV With Connectivity Outage Constraint
title_full Trajectory Optimization for Cellular-Enabled UAV With Connectivity Outage Constraint
title_fullStr Trajectory Optimization for Cellular-Enabled UAV With Connectivity Outage Constraint
title_full_unstemmed Trajectory Optimization for Cellular-Enabled UAV With Connectivity Outage Constraint
title_sort trajectory optimization for cellular-enabled uav with connectivity outage constraint
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description This paper studies the trajectory optimization problem of a single cellular-enabled unmanned aerial vehicle (UAV), taking into account the outage performance of the entire trajectory. To provide real-time control, it is critical for UAV to maintain reliable connectivity with the ground base station (GBS). We first consider the connectivity outage performance, which is defined as the sum of the time duration of the outage performance not meeting a predefined threshold during the entire UAV mission. Then we formulate a trajectory optimization problem to minimize the mission completion time, while ensuring a sum constraint of the connectivity outage performance. We show that the connectivity outage constraint can be transformed into a flying area constraint. Since the formulated problem is NP-hard, a low-complexity method is proposed to solve the problem by finding the shortest path in an undirected weighted graph with enlarged GBS coverage. Simulation results demonstrate the superiority of the proposed scheme over other state-of-the-art schemes, in terms of trajectory length and computational complexity.
topic Unmanned aerial vehicle (UAV)
trajectory optimization
cellular networks
url https://ieeexplore.ieee.org/document/8984324/
work_keys_str_mv AT yujiachen trajectoryoptimizationforcellularenableduavwithconnectivityoutageconstraint
AT dayuhuang trajectoryoptimizationforcellularenableduavwithconnectivityoutageconstraint
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