Adaptive communication power control for enhancing attack resilience in UAV networks

Linfeng Zhong, Lei Zhang, Hao Yang, Pengfei Chen, Qingwei Zhong, Fei Hu and Jin Huang
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Linfeng Zhong: Civil Aviation Flight University of China, Guanghan 618307, P. R. China†Chengdu GoldTel Industry Group Co., Ltd., Chengdu 611731, P. R. China‡University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
Lei Zhang: Civil Aviation Flight University of China, Guanghan 618307, P. R. China
Hao Yang: Civil Aviation Flight University of China, Guanghan 618307, P. R. China
Pengfei Chen: Civil Aviation Flight University of China, Guanghan 618307, P. R. China
Qingwei Zhong: Civil Aviation Flight University of China, Guanghan 618307, P. R. China
Fei Hu: �Civil Aviation Flight University of China Suining Flight College, 629001 Suining, P. R. China
Jin Huang: Civil Aviation Flight University of China, Guanghan 618307, P. R. China

International Journal of Modern Physics C (IJMPC), 2025, vol. 36, issue 10, 1-14

Abstract: A swarm of Unmanned Aerial Vehicles (UAVs) comprises multiple UAVs that are capable of completing tasks beyond the capabilities of a single UAV. Due to the unique challenges of UAV missions, these vehicles often operate far from base stations, making network connectivity crucial for the successful completion of UAV swarm missions. However, existing methods do not account for strategies to maintain the overall connectivity of the UAV network when nodes are under attack. To address this issue, we propose a method named Adaptive Communication Power Control (ACPC) that dynamically adjusts UAV communication power to mitigate potential connectivity losses caused by node failures or malicious attacks. This adjustment ensures that the network can maintain information exchange among the remaining UAVs even in the event of disruptions. Additionally, we introduce a novel evaluation method to assess the overall connectivity of the network and validate ACPC through simulations of UAV swarm missions where some UAVs experience failures. Using this evaluation method, we measured the network’s state before and after attacks and recovery and calculated the additional energy consumption required by the UAVs. The results indicate that our method can increase the resilience of the UAV network by up to 5.36 times, while only raising the total communication energy consumption to 1.53 times.

Keywords: Resilience; UAV swarm; complex networks; communication power control (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1142/S0129183124420087

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