A Multi-Timescale Cross-Layer Anti-Jamming Scheme Under Rule Guidance

Dynamic spectrum control is a viable anti-jamming scheme; however, frequency switching (FS) has relatively high time overhead in practice. Moreover, if the jamming variation cycle is shorter than that of the FS, it can cause communication degradation or even failure. Therefore, we employ both link layer FS and low-overhead physical layer actions for joint anti-jamming and establish distinct decision timescales based on these overheads. Specifically, we design distinct networks for different actions, utilizing cognitive information as rules to guide the agent optimization direction for resource deployment. Simulation results indicate that our method improves the throughput by 112.87% compared to the same timescale algorithm, which demonstrates the effectiveness of associating cross-layer actions at different timescales under highly dynamic interference conditions.

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Publication Details

Journal
IEEE Communications Letters
Published
2024-12-04
DOI
https://doi.org/10.1109/lcomm.2024.3510878
Citations
4
Primary Topic
Guidance and Control Systems
Type
article
Field-Weighted Citation Impact
5.20
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article

A Multi-Timescale Cross-Layer Anti-Jamming Scheme Under Rule Guidance

Jiangbo Si, Haoqin Zhao, Naofal Al‐Dhahir, Xiaoting Wang et al.
4 citations
IEEE Communications Letters
Guidance and Control Systems
5.20
article

A Multi-Timescale Cross-Layer Anti-Jamming Scheme Under Rule Guidance

Jiangbo Si, Haoqin Zhao, Naofal Al‐Dhahir, Xiaoting Wang, Zan Li
article en
4 citations

Abstract

Dynamic spectrum control is a viable anti-jamming scheme; however, frequency switching (FS) has relatively high time overhead in practice. Moreover, if the jamming variation cycle is shorter than that of the FS, it can cause communication degradation or even failure. Therefore, we employ both link layer FS and low-overhead physical layer actions for joint anti-jamming and establish distinct decision timescales based on these overheads. Specifically, we design distinct networks for different actions, utilizing cognitive information as rules to guide the agent optimization direction for resource deployment. Simulation results indicate that our method improves the throughput by 112.87% compared to the same timescale algorithm, which demonstrates the effectiveness of associating cross-layer actions at different timescales under highly dynamic interference conditions.

IEEE Communications LettersVol. 29(2)
Beijing University of Posts and Telecommunications (CN), Xidian University (CN), The University of Texas at Dallas (US), China Telecom (China) (CN)
Openalex Percentile: Top 5%
Guidance and Control Systems
5.20
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