Cooperative Jamming Detection Using Low-Rank Structure of Received Signal Matrix

TL;DR

This paper introduces cooperative jamming detection techniques leveraging the low-rank structure of received signal matrices, employing likelihood ratio tests and synthetic signal generation to improve detection accuracy in wireless networks.

Contribution

It proposes novel detection methods based on low-rank matrix structures and analytical false alarm performance analysis, enhancing robustness over existing techniques.

Findings

Detectors outperform existing methods in simulations

Effective false alarm control via analytical threshold adjustment

Robust detection across various network scenarios

Abstract

Wireless communication can be simply subjected to malicious attacks due to its open nature and shared medium. Detecting jamming attacks is the first and necessary step to adopt the anti-jamming strategies. This paper presents novel cooperative jamming detection methods that use the low-rank structure of the received signal matrix. We employed the likelihood ratio test to propose detectors for various scenarios. We regarded several scenarios with different numbers of friendly and jamming nodes and different levels of available statistical information on noise. We also provided an analytical examination of the false alarm performance of one of the proposed detectors, which can be used to adjust the detection threshold. We discussed the synthetic signal generation and the Monte Carlo (MC)-based threshold setting method, where knowledge of the distribution of the jamming-free signal, as well as several parameters such as noise variance and channel state information (CSI), is required to accurately generate synthetic signals for threshold estimation. Extensive simulations reveal that the proposed detectors outperform several existing methods, offering robust and accurate jamming detection in a collaborative network of sensing nodes.