Channel (broadcasting)

Orthogonality

Capon

Mathematics

Beamforming

Noise (video)

Algorithm

Image (mathematics)

Mathematical optimization

Artificial intelligence

Control (management)

Covariance matrix

Programming language

Geometry

SIGNAL (programming language)

Interference (communication)

Adaptive beamformer

Computer science

Control theory (sociology)

Telecommunications

IEEE Transactions on Vehicular Technology

To ensure link reliability and signal receiving quality, robust adaptive beamforming (RAB) is vital important in mobile communications. In this paper, we propose a new RAB algorithm based on interference-plus-noise covariance (INC) matrix reconstruction and steering vector (SV) estimation. In this method, the INC matrix is reconstructed by estimating all interferences SVs and powers, as well as the noise power. The interference SVs are estimated by using the Capon spatial spectrum together with robust Capon beamforming principle, subsequently the interference powers are estimated based on the orthogonality between different signal SVs. On the other hand, the desired signal SV is estimated via maximizing the beamformer output power by solving a quadratic convex optimization problem. The proposed algorithm only needs to know in advance the array geometry and angular sector, in which the desired signal lies. Simulation results indicate that the proposed algorithm outperforms the existing RAB techniques in terms of the overall performance in cases of various mismatches.

Covariance Matrix Reconstruction With Interference Steering Vector and Power Estimation for Robust Adaptive Beamforming