Research on Resource Allocation and Trajectory Optimization of a Multitask Unmanned Aerial Vehicles Assisted Communication Network

PEI Errong; LOU Yuhan; LI Yonggang; LI Wei

doi:10.11999/JEIT230974

Volume 46 Issue 7

Jul. 2024

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Article Navigation > Journal of Electronics & Information Technology > 2024 > 46(7): 2748-2756

PEI Errong, LOU Yuhan, LI Yonggang, LI Wei. Research on Resource Allocation and Trajectory Optimization of a Multitask Unmanned Aerial Vehicles Assisted Communication Network[J]. Journal of Electronics & Information Technology, 2024, 46(7): 2748-2756. doi: 10.11999/JEIT230974

Citation:

PEI Errong, LOU Yuhan, LI Yonggang, LI Wei. Research on Resource Allocation and Trajectory Optimization of a Multitask Unmanned Aerial Vehicles Assisted Communication Network[J]. Journal of Electronics & Information Technology, 2024, 46(7): 2748-2756. doi: 10.11999/JEIT230974

Citation:

PEI Errong, LOU Yuhan, LI Yonggang, LI Wei. Research on Resource Allocation and Trajectory Optimization of a Multitask Unmanned Aerial Vehicles Assisted Communication Network[J]. Journal of Electronics & Information Technology, 2024, 46(7): 2748-2756. doi: 10.11999/JEIT230974

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Research on Resource Allocation and Trajectory Optimization of a Multitask Unmanned Aerial Vehicles Assisted Communication Network

doi: 10.11999/JEIT230974

1.
School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2.
Chongqing Jinmei Communication Co., Ltd., Chongqing 400035, China

Funds: The National Natural Science Foundation of China (62071077), Chongqing Chengyu Science and Technology Innovation Project (KJCXZD2020026)

Received Date: 2023-09-06
Rev Recd Date: 2024-01-25

Available Online: 2024-02-27

Publish Date: 2024-07-29

Abstract

Abstract

Unmanned Aerial Vehicles (UAV) loaded with various payloads can achieve multiple tasks such as sensing, communication, and computing, and are often deployed in fields such as Data Acquisition (DA) and auxiliary computing. However, so far, the vast majority of research has only focused on single function drone resource allocation and trajectory optimization, and the problem of multi task oriented drone resource allocation and trajectory optimization has not been solved yet. Therefore, an allocation strategy for optimizing drone communication network resources is proposed that comprehensively considers drone data acquisition, data broadcasting, and computing task offloading. The aim is to maximize user offloading by jointly optimizing transmission duty cycle, user transmission power, and drone trajectory, while meeting the real-time broadcast of target location data collection. In order to solve the problem of multivariable coupled optimization, an efficient iterative optimization algorithm based on Block Coordinate Descent (BCD) and Successive Convex Approximate (SCA) is proposed. The coupled optimization problem is decomposed into three sub problems for iterative optimization. Finally, a large number of simulation results show that the algorithm outperforms other testing schemes in terms of fairness and total offloading computation.
- Unmanned Aerial Vehicle (UAV) communication,
- Mobile Edge Computing (MEC),
- Data acquisition,
- Convex optimization

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References(18)

References

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