Deployment and Networking Methods of UAV Swarm in Jamming Environments Based on Game Theory

HAN Chen; LIU Aijun; AN Kang; TONG Xinhai; LIANG Xiaohu

doi:10.11999/JEIT210992

Volume 44 Issue 3

Mar. 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(3): 860-870

HAN Chen, LIU Aijun, AN Kang, TONG Xinhai, LIANG Xiaohu. Deployment and Networking Methods of UAV Swarm in Jamming Environments Based on Game Theory[J]. Journal of Electronics & Information Technology, 2022, 44(3): 860-870. doi: 10.11999/JEIT210992

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HAN Chen, LIU Aijun, AN Kang, TONG Xinhai, LIANG Xiaohu. Deployment and Networking Methods of UAV Swarm in Jamming Environments Based on Game Theory[J]. Journal of Electronics & Information Technology, 2022, 44(3): 860-870. doi: 10.11999/JEIT210992

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Deployment and Networking Methods of UAV Swarm in Jamming Environments Based on Game Theory

doi: 10.11999/JEIT210992

HAN Chen¹,
LIU Aijun^{2
,
,},
AN Kang¹,
TONG Xinhai²,
LIANG Xiaohu^{2, 3}

1.
The 63th Institute, National University of Defense Technology, Nanjing 210007, China
2.
College of Communications Engineering, Army Engineering University, Nanjing 210007, China
3.
The School of Information Science and Engineering, Southeast University, Nanjing 210018, China

Funds: The National Key Research and Development Program of China (2018YFB1801103), The National Natural Science Foundation of China (61901502), The Natural Science Foundation on Frontier Leading Technology Basic Research Project of Jiangsu Province (BK20192002), The National Postdoctoral Program for Innovative Talents (BX20200101)

Received Date: 2021-09-16
Accepted Date: 2022-02-16
Rev Recd Date: 2022-02-16

Available Online: 2022-02-28

Publish Date: 2022-03-28

Abstract

Abstract

A deployment and networking methods of Unmanned Aerial Vehicle (UAV) swarm based on game theory in the jamming environments is investigated in this paper. Firstly, a Congestion-game based UAV swarm Deployment algorithm (CUD）is proposed. Each UAV can autonomously optimize its position through limited interaction with adjacent UAVs to increase the amount of collected data and enhance the anti-jamming capabilities. Secondly, a UAV Swarm Anti-jamming Coalition Formation algorithm (USACF) is proposed, which enables the UAV swarm to form dynamic sub-networks in a distributed way under the threat of hostile jamming, thus improving the transmission performance and enhancing the robustness and reliability of the UAV networks. Furthermore, it is proved theoretically that the proposed game model can achieve a stable Nash equilibrium with the aid of exact potential game theory. Finally, simulation results verify that the proposed algorithms have obvious performance improvement compared with the conventional algorithms.
- Unmanned Aerial Vehicle (UAV) swarm,
- Anti-jamming,
- Game theory

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References(36)

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