Joint Power and 3D Trajectory Optimization for UAV-enabled Wireless Powered Communication Networks with Obstacles

Unmanned aerial vehicle (UAV)-enabled wireless powered communication networks (WPCNs) are promising technologies in 5G/6G wireless communications, while there are several challenges about UAV power allocation and scheduling to enhance the energy utilization efficiency, considering the existence of o...

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Veröffentlicht in:	IEEE transactions on communications Jg. 71; H. 4; S. 1
Hauptverfasser:	Pan, Hongyang, Liu, Yanheng, Sun, Geng, Fan, Junsong, Liang, Shuang, Yuen, Chau
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.04.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Autonomous aerial vehicles Barriers Communication networks Communications networks Efficiency energy consumption Energy utilization Genetic algorithms non-dominated sorting genetic algorithm-II Normal distribution Operators (mathematics) Optimization Particle swarm optimization Power management Renewable energy sources Resource management Sorting algorithms Three-dimensional displays Trajectory optimization unmanned aerial vehicle Unmanned aerial vehicles Uplink Wireless communications Wireless networks Wireless powered communication networks
ISSN:	0090-6778, 1558-0857
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Abstract	Unmanned aerial vehicle (UAV)-enabled wireless powered communication networks (WPCNs) are promising technologies in 5G/6G wireless communications, while there are several challenges about UAV power allocation and scheduling to enhance the energy utilization efficiency, considering the existence of obstacles. In this work, we consider a UAV-enabled WPCN scenario that a UAV needs to cover the ground wireless devices (WDs). During the coverage process, the UAV needs to collect data from the WDs and charge them simultaneously. To this end, we formulate a joint-UAV power and three-dimensional (3D) trajectory optimization problem (JUPTTOP) to simultaneously increase the total number of the covered WDs, increase the time efficiency, and reduce the total flying distance of UAV so as to improve the energy utilization efficiency in the network. Due to the difficulties and complexities, we decompose it into two sub optimization problems, which are the UAV power allocation optimization problem (UPAOP) and UAV 3D trajectory optimization problem (UTTOP), respectively. Then, we propose an improved non-dominated sorting genetic algorithm-II with K -means initialization operator and Variable dimension mechanism (NSGA-II-KV) for solving the UPAOP. For UTTOP, we first introduce a pretreatment method, and then use an improved particle swarm optimization with Normal distribution initialization, Genetic mechanism, Differential mechanism and Pursuit operator (PSO-NGDP) to deal with this sub optimization problem. Simulation results verify the effectiveness of the proposed strategies under different scales and settings of the networks.
AbstractList	Unmanned aerial vehicle (UAV)-enabled wireless powered communication networks (WPCNs) are promising technologies in 5G/6G wireless communications, while there are several challenges about UAV power allocation and scheduling to enhance the energy utilization efficiency, considering the existence of obstacles. In this work, we consider a UAV-enabled WPCN scenario that a UAV needs to cover the ground wireless devices (WDs). During the coverage process, the UAV needs to collect data from the WDs and charge them simultaneously. To this end, we formulate a joint-UAV power and three-dimensional (3D) trajectory optimization problem (JUPTTOP) to simultaneously increase the total number of the covered WDs, increase the time efficiency, and reduce the total flying distance of UAV so as to improve the energy utilization efficiency in the network. Due to the difficulties and complexities, we decompose it into two sub optimization problems, which are the UAV power allocation optimization problem (UPAOP) and UAV 3D trajectory optimization problem (UTTOP), respectively. Then, we propose an improved non-dominated sorting genetic algorithm-II with K -means initialization operator and Variable dimension mechanism (NSGA-II-KV) for solving the UPAOP. For UTTOP, we first introduce a pretreatment method, and then use an improved particle swarm optimization with Normal distribution initialization, Genetic mechanism, Differential mechanism and Pursuit operator (PSO-NGDP) to deal with this sub optimization problem. Simulation results verify the effectiveness of the proposed strategies under different scales and settings of the networks. Unmanned aerial vehicle (UAV)-enabled wireless powered communication networks (WPCNs) are promising technologies in 5G/6G wireless communications, while there are several challenges about UAV power allocation and scheduling to enhance the energy utilization efficiency, considering the existence of obstacles. In this work, we consider a UAV-enabled WPCN scenario that a UAV needs to cover the ground wireless devices (WDs). During the coverage process, the UAV needs to collect data from the WDs and charge them simultaneously. To this end, we formulate a joint-UAV power and three-dimensional (3D) trajectory optimization problem (JUPTTOP) to simultaneously increase the total number of the covered WDs, increase the time efficiency, and reduce the total flying distance of UAV so as to improve the energy utilization efficiency in the network. Due to the difficulties and complexities, we decompose it into two sub optimization problems, which are the UAV power allocation optimization problem (UPAOP) and UAV 3D trajectory optimization problem (UTTOP), respectively. Then, we propose an improved non-dominated sorting genetic algorithm-II with [Formula Omitted]-means initialization operator and Variable dimension mechanism (NSGA-II-KV) for solving the UPAOP. For UTTOP, we first introduce a pretreatment method, and then use an improved particle swarm optimization with Normal distribution initialization, Genetic mechanism, Differential mechanism and Pursuit operator (PSO-NGDP) to deal with this sub optimization problem. Simulation results verify the effectiveness of the proposed strategies under different scales and settings of the networks.
Author	Yuen, Chau Liu, Yanheng Fan, Junsong Liang, Shuang Pan, Hongyang Sun, Geng
Author_xml	– sequence: 1 givenname: Hongyang surname: Pan fullname: Pan, Hongyang organization: College of Computer Science and Technology, Jilin University, Changchun, China – sequence: 2 givenname: Yanheng orcidid: 0000-0001-9826-5266 surname: Liu fullname: Liu, Yanheng organization: College of Computer Science and Technology, Jilin University, Changchun, China – sequence: 3 givenname: Geng orcidid: 0000-0001-7802-4908 surname: Sun fullname: Sun, Geng organization: College of Computer Science and Technology, Jilin University, Changchun, China – sequence: 4 givenname: Junsong surname: Fan fullname: Fan, Junsong organization: College of Computer Science and Technology, Jilin University, Changchun, China – sequence: 5 givenname: Shuang orcidid: 0000-0001-7651-505X surname: Liang fullname: Liang, Shuang organization: School of Information Science and Technology, Northeast Normal University, Changchun, China – sequence: 6 givenname: Chau orcidid: 0000-0002-9307-2120 surname: Yuen fullname: Yuen, Chau organization: Engineering Product Development (EPD) Pillar, Singapore University of Technology and Design, Singapore
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SubjectTerms	Autonomous aerial vehicles Barriers Communication networks Communications networks Efficiency energy consumption Energy utilization Genetic algorithms non-dominated sorting genetic algorithm-II Normal distribution Operators (mathematics) Optimization Particle swarm optimization Power management Renewable energy sources Resource management Sorting algorithms Three-dimensional displays Trajectory optimization unmanned aerial vehicle Unmanned aerial vehicles Uplink Wireless communications Wireless networks Wireless powered communication networks
Title	Joint Power and 3D Trajectory Optimization for UAV-enabled Wireless Powered Communication Networks with Obstacles
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