Jun Wang
Dalian Maritime University
9 Papers
2 Citations
Jun Wang is an academic researcher from Dalian Maritime University. The author has contributed to research in topics: Computer science & Resource allocation. The author has an hindex of 4, co-authored 7 publications.
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Papers
Collaborative Design of Multi-UAV Trajectory and Resource Scheduling for 6G-Enabled Internet of Things
Jun Wang,Zhenyu Na,Xin Liu +2 more
TL;DR: A multi-UAV wireless powered communication (WPC) system for 6G-enabled Internet of Things that synergistically optimizing UAV-user association, sub-slot duration, user transmit power and multi- UAV trajectory, and maximize the minimum average achievable rate among all users is proposed.
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Join trajectory optimization and communication design for UAV-enabled OFDM networks
Zhenyu Na,Jun Wang,Chungang Liu,Mingxiang Guan,Zihe Gao +4 more
- 01 Mar 2020
TL;DR: A joint UAV trajectory optimization and communication design scheme is proposed based on Simultaneous Wireless Information and Power Transfer (SWIPT) technology and results demonstrate that the proposed algorithm has good convergence and the proposed UAV-enabled OFDM network has better performance.
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UAV-assisted wireless powered Internet of Things: Joint trajectory optimization and resource allocation
Zhenyu Na,Mengshu Zhang,Jun Wang,Zihe Gao +3 more
- 01 Mar 2020
TL;DR: A joint UAV trajectory optimization and resource allocation scheme based on OFDM is proposed and results show that the proposed scheme not only significantly enhances the minimum achievable rate, but also works well for two flight modes.
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UAV-Based Wide-Area Internet of Things: An Integrated Deployment Architecture
TL;DR: In this paper, an unmanned aerial vehicle (UAV)-based wide-area Internet of Things (WAIoT) deployment framework was established by considering three typical scenarios including power outage, massive user connections, and information island relief.
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Joint trajectory and power optimization for UAV-relay-assisted Internet of Things in emergency
TL;DR: Simulation results show that the proposed iterative algorithm can not only optimize the UAV trajectory, but also effectively improve the downlink achievable sum rate compared with the benchmark schemes.
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