DQN-based decentralized multi-agent JSAP resource allocation for UAV swarm communication

doi:10.23919/JSEE.2023.000045

Journal of Systems Engineering and Electronics ›› 2023, Vol. 34 ›› Issue (2): 289-298.doi: 10.23919/JSEE.2023.000045

• • 上一篇

收稿日期:2021-12-03 出版日期:2023-04-18 发布日期:2023-04-18

DQN-based decentralized multi-agent JSAP resource allocation for UAV swarm communication

Jie LI(), Xiaoyu DANG(), Sai LI()

¹ College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

Received:2021-12-03 Online:2023-04-18 Published:2023-04-18
Contact: Xiaoyu DANG E-mail:lj2022@nuaa.edu.cn;dang@nuaa.edu.cn;li_sai@nuaa.edu.cn
About author:
LI Jie was born in 1985. She received her B.S. degree in electronic information and engineering and M.S. degree in signal and information processing from University of Jinan, Ji’nan, China, in 2009 and 2011, respectively. She is now studying for her Ph.D. degree in Nanjing University of Aeronautics and Astronautics. Her research interests are UAV swarming communications, wireless communication, and signal processing. E-mail: lj2022@nuaa.edu.cn

DANG Xiaoyu was born in 1973. He received his Ph.D. degree in electrical engineering from Brigham Young University，Provo, UT, USA. He is a professor in the College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics. His research interests include deep space communications, satellite positioning and navigation, unmanned aerial vehicle swarm communications, and aeronautical and astronautical telemetry. E-mail: dang@nuaa.edu.cn

LI Sai was born in 1993. He received his B.S. degree in electronic science and technology from Henan University of Engineering, in 2016, and M.S. degree in electronic science and technology from North China University of Technology, in 2019. He is pursuing his Ph.D. degree in Nanjing University of Aeronautics and Astronautics. His research interests include unmanned aerial vehicle communication and non-orthogonal multiple access. E-mail: li_sai@nuaa.edu.cn
Supported by:
This work was supported by the National Natural Science Foundation of China (62031017;61971221)

摘要/Abstract

Abstract:

It is essential to maximize capacity while satisfying the transmission time delay of unmanned aerial vehicle (UAV) swarm communication system. In order to address this challenge, a dynamic decentralized optimization mechanism is presented for the realization of joint spectrum and power (JSAP) resource allocation based on deep Q-learning networks (DQNs). Each UAV to UAV (U2U) link is regarded as an agent that is capable of identifying the optimal spectrum and power to communicate with one another. The convolutional neural network, target network, and experience replay are adopted while training. The findings of the simulation indicate that the proposed method has the potential to improve both communication capacity and probability of successful data transmission when compared with random centralized assignment and multichannel access methods.

Key words: joint spectrum and power (JSAP), unmanned aerial vehicle (UAV) swarm communication, deep Q-learning network (DQN), UAV to UAV (U2U)

. [J]. Journal of Systems Engineering and Electronics, 2023, 34(2): 289-298.

Jie LI, Xiaoyu DANG, Sai LI. DQN-based decentralized multi-agent JSAP resource allocation for UAV swarm communication[J]. Journal of Systems Engineering and Electronics, 2023, 34(2): 289-298.

图/表 11

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Parameters	Value
Carrier frequency/GHz	1
Number of spectrum band	20
Bandwidth/Mbps	2
Maximum transmission power/dBm	23
Gaussian noise power/dBm	−96
Maximum UAV speed/(m·s⁻¹)	10

DQN-based decentralized multi-agent JSAP resource allocation for UAV swarm communication

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