Join trajectory optimization and communication design for UAV-enabled OFDM networks

被引:46
|
作者
Na, Zhenyu [1 ]
Wang, Jun [1 ]
Liu, Chungang [2 ]
Guan, Mingxiang [3 ]
Gao, Zihe [4 ]
机构
[1] Dalian Maritime Univ, Sch Informat Sci & Technol, Dalian 116026, Peoples R China
[2] Hebei Normal Univ, Coll Career Technol, Shijiazhuang 050024, Hebei, Peoples R China
[3] Shenzhen Inst Informat Technol, Sch Elect Commun Technol, Shenzhen 518000, Peoples R China
[4] China Acad Space Technol, Res Ctr Inst Telecommun Satellite, Beijing 100081, Peoples R China
关键词
UAV; OFDM; SWIFT; Trajectory optimization; Resource allocation; SIMULTANEOUS WIRELESS INFORMATION; THROUGHPUT MAXIMIZATION; ALLOCATION; SUBCARRIER;
D O I
10.1016/j.adhoc.2019.102031
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Due to the advantages of high mobility, flexible maneuverability and fast deployment, Unmanned Aerial Vehicle (UAV), which can be usually served as aerial communication platform, not only supports information transmission in the Internet of things (IoT), but also provides reliable power supplement for low-power wireless devices. Considering an UAV-enabled Orthogonal Frequency Division Multiplexing (OFDM) network where subcarriers are divided into two groups for information transmission and energy harvesting, respectively, a joint UAV trajectory optimization and communication design scheme is proposed based on Simultaneous Wireless Information and Power Transfer (SWIPT) technology. Under the given average harvested energy for users, the objective of the scheme is to maximize the average achievable rate for all users by jointly optimizing UAV trajectory, user scheduling, subcarrier and power allocation. To solve the formulated optimization problem, it is transformed into two subproblems to optimize resource allocation and UAV trajectory, respectively. The former is a mixed integer non-convex optimization problem. To solve it, a three-variable alternative iteration algorithm is proposed to obtain the optimal user scheduling, subcarrier and power allocation. Since the latter is non-convex, it can be transformed into convex optimization problem by relaxing objective function and constraint to obtain the optimal trajectory. Simulation results demonstrate that the proposed algorithm has good convergence and the proposed UAV-enabled OFDM network has better performance. (C) 2019 Elsevier B.V. All rights reserved.
引用
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页数:10
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