Path Planning and Time Scheduling for UAV-Assisted Joint Communication and Localization System

Uncrewed aerial vehicle (UAV)-assisted joint communication and localization (JCAL) system have great potential and capacity to make future Internet of Things efficient, safe, smart, reliable, and sustainable. Generally, the traditional UAV path planning methods set the flying duration and hovering duration of UAVs as constants, and ignore the importance of UAV operation time in emergency rescue and other scenarios. In this article, we consider the path planning and time scheduling problem of UAV-assisted JCAL system for minimizing the UAV operation time under the constraints of the localization accuracy, communication message, and energy loss. Specifically, we first formulate path planning and time scheduling problem for UAV-assisted JCAL system and derive Cramér-Rao bound (CRB) as the localization accuracy constraint. The variables in the constraints of localization accuracy, communication overhead, and energy loss are deeply coupled, which leads to nonconvex optimization problems. Next, to solve the high nonconvex problem, we divide the original problem into two subproblems, i.e., time scheduling subproblem and path planning subproblem. We use equivalent convex transformation and successive convex approximation (SCA) to transform the nonconvex constraints into convex forms for solving the subproblems, respectively. Lastly, aiming to the robust problem of target and channel parameters, we convert the robust constraints into convex constraint forms by equivalent proof and S-Procedure. On this basis, we develop a robust algorithm for solving the uncertainty of target and channel parameters. Simulation results verify the feasibility of the proposed methods.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-11-20
DOI
https://doi.org/10.1109/jiot.2024.3504397
Citations
1
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
1.30

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article

Path Planning and Time Scheduling for UAV-Assisted Joint Communication and Localization System

Zhiyuan Feng, Fengye Hu, Yanping Zhao, Bo Wang
1 citations
IEEE Internet of Things Journal
UAV Applications and Optimization
1.30
article

Path Planning and Time Scheduling for UAV-Assisted Joint Communication and Localization System

Zhiyuan Feng, Fengye Hu, Yanping Zhao, Bo Wang
article en
1 citations

Abstract

Uncrewed aerial vehicle (UAV)-assisted joint communication and localization (JCAL) system have great potential and capacity to make future Internet of Things efficient, safe, smart, reliable, and sustainable. Generally, the traditional UAV path planning methods set the flying duration and hovering duration of UAVs as constants, and ignore the importance of UAV operation time in emergency rescue and other scenarios. In this article, we consider the path planning and time scheduling problem of UAV-assisted JCAL system for minimizing the UAV operation time under the constraints of the localization accuracy, communication message, and energy loss. Specifically, we first formulate path planning and time scheduling problem for UAV-assisted JCAL system and derive Cramér-Rao bound (CRB) as the localization accuracy constraint. The variables in the constraints of localization accuracy, communication overhead, and energy loss are deeply coupled, which leads to nonconvex optimization problems. Next, to solve the high nonconvex problem, we divide the original problem into two subproblems, i.e., time scheduling subproblem and path planning subproblem. We use equivalent convex transformation and successive convex approximation (SCA) to transform the nonconvex constraints into convex forms for solving the subproblems, respectively. Lastly, aiming to the robust problem of target and channel parameters, we convert the robust constraints into convex constraint forms by equivalent proof and S-Procedure. On this basis, we develop a robust algorithm for solving the uncertainty of target and channel parameters. Simulation results verify the feasibility of the proposed methods.

IEEE Internet of Things JournalVol. 12(7)
Jilin University (CN)
National Natural Science Foundation of China, Jilin Province Key R&D Plan Project
Openalex Percentile: Top 12%
UAV Applications and Optimization
1.30
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