Adaptive beamforming algorithms for cancellation of multiple interference signals

Abstract

This paper proposes a fast Minimum-Variance-Distortionless-Response (MVDR) beamforming algorithm for an antenna array for cancellation of multiple interference signals. The proposed algorithm uses Sample-Average Estimate (SAE) of the data covariance matrix and reduces its computational effort by applying the Matrix-Inversion-Lemma (MIL) to its covariance Matrix Inversion (MI) operation. The proposed algorithm is compared to two SAE-based algorithms: the Sample Matrix Inversion (SMI) algorithm that requires an MI operation and the Auxiliary Vector (AV) algorithm that does not need an MI operation. A non-SAE based algorithm using the Least Mean Square (LMS) method is also included for comparison. Simulation results show that the proposed algorithm converges slower than the SMI scheme but outperforms the AV and LMS schemes during the transient phase. Once convergence is achieved, the proposed algorithm converges to a better Mean Square Error than the rest of the algorithms evaluated.