Enhancing Resilience Against Jamming Attacks: A Cooperative Anti-Jamming Method Using Direction Estimation

2025-07-19

AI Summary

To address the insufficient robustness of wireless communications under strong interference and rapid channel fading, this paper proposes an interference-resilient method based on multi-node collaborative sensing and channel direction estimation. The approach innovatively integrates eigenvector-based (EV) spatial direction estimation from pilot signals, distributed degrees-of-freedom management, and cooperative interference suppression. It maintains high performance even under stringent conditions—such as short channel coherence time and dynamically moving interferers. Experimental results demonstrate that the method incurs only a 0.7 dB SNR penalty relative to the interference-free case; moreover, when the number of sensing nodes significantly exceeds the number of interferers, its interference mitigation performance approaches the theoretical upper bound achievable with perfect channel state information (CSI). This work establishes a new paradigm for low-overhead, highly robust dynamic interference mitigation in wireless systems.

Technology Category

• Intelligent Robots: State Estimation
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Machine Learning: Matrix & Tensor Methods

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Security and Privacy: Large-scale security measurements

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 to the case without jamming especially when the number of SNs is significantly larger than the number of jamming nodes (JNs). Moreover, the extension of the proposed method can handle multiple jammers at the expense of degrees of freedom (DoF). We also investigate the method's ability to remain robust in fast-fading channels with different coherence times. Our proposed approach demonstrates good resilience, particularly when the ratio of the channel's coherence time to the time frame is small. This is especially important in the case of mobile jammers with large Doppler shifts.

Problem

• Develop cooperative anti-jamming method to counter wireless jamming attacks
• Estimate channel direction using eigenvector method without perfect CSI
• Maintain resilience in fast-fading channels against mobile jammers

Innovation

• Cooperative anti-jamming using multiple sensing nodes
• Eigenvector method for direction estimation
• Robust performance in fast-fading channels