A Novel Anti-Jamming Decision-Making Algorithm Based on Knowledge Graph Technology

Autor: Yingtao Niu, Xijin Feng, Shaoqin Kou, Peng Xiang
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Applied Sciences, Vol 12, Iss 10, p 4960 (2022)
Druh dokumentu: article
ISSN: 2076-3417
DOI: 10.3390/app12104960
Popis: Wireless communications are increasingly vulnerable to malicious jamming attacks due to the inherent openness and broadcast nature. In this regard, a novel anti-jamming scheme based on knowledge graph is proposed in this paper, where the knowledge graph which contains the prior knowledge of the commonly-used jamming patterns is utilized to make the fast anti-jamming decision with low complexity. Specifically, for the known jamming patterns, the anti-jamming strategy is directly extracted based on the search from the knowledge graph by using the sensing information. On the other hand, for the unknown jamming patterns, a time-frequency domain feature extraction method is first proposed to extract the jamming feature and match the jamming patterns in the knowledge graph. As such, multiple anti-jamming strategies can be obtained by the knowledge graph search. Finally, the optimal strategy can be achieved by the two communication decision criteria-based strategy fusion. The simulation results showed that the time-frequency domain feature extraction method can well extract the time-frequency domain feature of the jamming pattern, and the proposed algorithm has high decision accuracy and robustness.
Databáze: Directory of Open Access Journals