Anti-Main-Lobe Jamming Beamforming With Covariance Matrix Reconstruction for Wireless Communication Systems Under Jamming Attacks

Abstract

This paper investigates an eigenpair substitution-based covariance matrix reconstruction beamforming algorithm to achieve reliable wireless communication under interference attacks. Our objective is to accurately eliminate main and side lobe interferences in the communication scenario without affecting the communication signal. Specifically, we design a precise interference-plus-noise (IPN) covariance matrix based on the received signals. The interference covariance matrix is obtained using the integration method at first, and then the eigenpair substitution is utilized to further eliminate the communication signal components in the interference covariance matrix. After that, diagonal loading is performed on the interference covariance matrix to obtain the IPN covariance matrix for designing the beamforming vector. Additionally, we derive the correlation between eigenvectors and signal steering vectors, thereby validating the rationale for employing eigenpair substitution to eliminate communication signal components from the IPN covariance matrix. Simulation results show that the proposed algorithm is superior to other benchmark algorithms, especially when the signal-to-noise ratio is high or the number of snapshots is small.