Author
Listed:
- Wenpeng Wu
(Rocket Force University of Engineering, Xi’an 710025, China
PLA 967XX Unit, Henan, China)
- Zhenhua Wei
(Rocket Force University of Engineering, Xi’an 710025, China
School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009, China)
- Haiyang You
(Rocket Force University of Engineering, Xi’an 710025, China)
- Zhaoguang Zhang
(Rocket Force University of Engineering, Xi’an 710025, China)
- Chenxi Li
(Rocket Force University of Engineering, Xi’an 710025, China)
- Jianwei Zhan
(Rocket Force University of Engineering, Xi’an 710025, China)
- Shan Zhao
(School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009, China)
Abstract
Air–ground joint jamming enables three-dimensional, distributed jamming configurations, making it effective against air–ground communication networks with complex, dynamically adjustable links. Once the jamming layout is fixed, dynamic jamming power scheduling becomes essential to conserve energy and prolong jamming duration. However, existing methods suffer from poor applicability in such scenarios, primarily due to their sparse deployment and adversarial nature. To address this limitation, this paper develops a set of mathematical models and a dedicated algorithm for air–ground communication countermeasures. Specifically, we (1) randomly select communication nodes to determine the jammer operation sequence; (2) schedule the number of active jammers by sorting transmission path losses in ascending order; and (3) estimate jamming effects using electromagnetic wave propagation characteristics to adjust jamming power dynamically. This approach formally converts the original dynamic, stochastic jamming resource scheduling problem into a static, deterministic one via cognitive certainty of dynamic parameters and deterministic modeling of stochastic factors—enabling rapid adaptation to unknown, dynamic communication power strategies and resolving the coordination challenge in air–ground joint jamming. Experimental results demonstrate that the proposed Transmission Loss Ordering Algorithm (TLOA) extends the system operating duration by up to 41.6% compared to benchmark methods (e.g., genetic algorithm).
Suggested Citation
Wenpeng Wu & Zhenhua Wei & Haiyang You & Zhaoguang Zhang & Chenxi Li & Jianwei Zhan & Shan Zhao, 2026.
"TLOA: A Power-Adaptive Algorithm Based on Air–Ground Cooperative Jamming,"
Future Internet, MDPI, vol. 18(2), pages 1-23, February.
Handle:
RePEc:gam:jftint:v:18:y:2026:i:2:p:81-:d:1855525
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