Enhancing Resilience Against Jamming Attacks: A Cooperative Anti-Jamming Method Using Direction Estimation
Amir Mehrabian, Georges Kaddoum

TL;DR
This paper introduces a cooperative anti-jamming method (CAJ) using eigenvector-based direction estimation, which effectively mitigates jamming in wireless networks, maintaining high performance even under severe and fast-changing jamming conditions.
Contribution
The paper proposes a novel EV-based direction estimation technique for cooperative anti-jamming, demonstrating its effectiveness and robustness in various challenging scenarios.
Findings
Performance close to perfect CSI with sufficient pilot symbols
Only 0.7 dB degradation under strong jamming with many sensing nodes
Robustness in fast-fading channels and against mobile jammers
Abstract
The inherent vulnerability of wireless communication necessitates strategies to enhance its security, particularly in the face of jamming attacks. This paper uses the collaborations of multiple sensing nodes (SNs) in the wireless network to present a cooperative anti-jamming approach (CAJ) designed to neutralize the impact of jamming attacks. We propose an eigenvector (EV) method to estimate the direction of the channel vector from pilot symbols. Through our analysis, we demonstrate that with an adequate number of pilot symbols, the performance of the proposed EV method is comparable to the scenario where the perfect channel state information (CSI) is utilized. Both analytical formulas and simulations illustrate the excellent performance of the proposed EV-CAJ under strong jamming signals. Considering severe jamming, the proposed EV-CAJ method exhibits only a 0.7 dB degradation compared…
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