UAV Trajectory Planning and Resource Joint Optimization Method Based on Content-aware

ZHU Xiaorong; ZHANG Wenjin; ZHAO Lingyu; LIU Xu; REN Wei

doi:10.11999/JEIT220761

Volume 45 Issue 5

May 2023

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Article Navigation > Journal of Electronics & Information Technology > 2023 > 45(5): 1644-1650

ZHU Xiaorong, ZHANG Wenjin, ZHAO Lingyu, LIU Xu, REN Wei. UAV Trajectory Planning and Resource Joint Optimization Method Based on Content-aware[J]. Journal of Electronics & Information Technology, 2023, 45(5): 1644-1650. doi: 10.11999/JEIT220761

Citation:

ZHU Xiaorong, ZHANG Wenjin, ZHAO Lingyu, LIU Xu, REN Wei. UAV Trajectory Planning and Resource Joint Optimization Method Based on Content-aware[J]. Journal of Electronics & Information Technology, 2023, 45(5): 1644-1650. doi: 10.11999/JEIT220761

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UAV Trajectory Planning and Resource Joint Optimization Method Based on Content-aware

doi: 10.11999/JEIT220761

1.
Jiangsu Key Laboratory of Wireless Communications, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
2.
Nanjing Bailian Information Technology Co., Ltd., Nanjing 210003, China

Funds: The National Natural Science Foundation of China (61871237, 92067101), The Program to Cultivate Middle-aged and Young Science Leaders of Universities of Jiangsu Province and Key Research and Development Plan of Jiangsu Province (BE2021013-3, BE2020084-3)

Received Date: 2022-06-13
Rev Recd Date: 2022-07-09

Available Online: 2022-07-25

Publish Date: 2023-05-10

Abstract

Abstract

In view of the surge in data traffic and the diversified needs of users in the future 6G network, using UAV to assist the cellular network can provide users with better services. This paper proposes a UAV trajectory planning and resource allocation joint optimization method based on content-aware. Hot content is cached on UAV. Under the condition of satisfying the user’s content demand, user association and UAV trajectory are jointly optimized to maximize the minimum average service rate of users. Since the established optimization problem is non-convex, a block coordinate descent method is proposed to decompose the original problem into two sub-problems and the trajectory planning problem is solved by continuous convex optimization method. The simulation results show that the proposed method can effectively improve the minimum user average service rate and the network depth coverage level.
- UAV communication,
- Trajectory planning,
- Content cache,
- Continuous convex optimization

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References(13)

References

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