Know Thy Enemy: An Opponent Modeling-Based Anti-Intelligent Jamming Strategy Beyond Equilibrium Solutions

Li, Wen; Xu, Yuhua; Chen, Jin; Yuan, Hongcheng; Han, Hao; Xu, Yifan; Feng, Zhibin

doi:10.1109/lwc.2022.3219434

Cited by 4 publications

(1 citation statement)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The control competition over the electromagnetic spectrum between communication terminals requires a decision-making scheme that can assist or predict such struggles. Game theory [3] has become a valuable mathematical tool to tackle anti-jamming issues. It enables the system to select the optimal policies in confrontational or conflict situations.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Frequency Decision Communication with Two-Agent Deep Reinforcement Learning

Liu,

Shi,

Wang

2023

Electronics

View full text Add to dashboard Cite

Traditional intelligent frequency-hopping anti-jamming technologies typically assume the presence of an ideal control channel. However, achieving this ideal condition in real-world confrontational environments, where the control channel can also be jammed, proves to be challenging. Regrettably, in the absence of a reliable control channel, the autonomous synchronization of frequency decisions becomes a formidable task, primarily due to the dynamic and heterogeneous nature of the transmitter and receiver’s spectral states. To address this issue, a novel communication framework for intelligent frequency decision is introduced, which operates without the need for negotiations. Furthermore, the frequency decision challenge between two communication terminals is formulated as a stochastic game, with each terminal’s utility designed to meet the requirements of a potential game. Subsequently, a two-agent deep reinforcement learning algorithm for best-response policy learning is devised to enable both terminals to achieve synchronization while avoiding jamming signals. Simulation results demonstrate that once the proposed algorithm converges, both communication terminals can effectively evade jamming signals. In comparison to existing similar algorithms, the throughput performance of this approach remains largely unaffected, with only a slightly extended convergence time. Notably, this performance is achieved without the need for negotiations, making the presented algorithm better suited for realistic scenarios.

show abstract

Section: Introductionmentioning

confidence: 99%