Adaptive beamforming via steering vector estimation
In the era of 5G, the problem of spectrum congestion has become serious, especially with the popularity of smart devices. Hence, it is challengeable for adaptive beamforming to achieve effective interference suppression in complex propagation environments. In addition, the large number of antennas adopted in massive MIMO systems are also eager to face the array mismatch problem, which degrade the performance of adaptive beamformers.
Both interference multipath and array mismatch will degrade the accuracy of interference-plus-noise covariance matrix reconstruction. Due to the fact that the adaptive beamformer is a function of interference-plus-noise covariance matrix and desired signal steering vector, we consider improving the performance of adaptive beamformer by estimating the steering vector of the desired signal.
In detail, maximizing the Capon beamformer output power
leads to the following convex optimization problem
where is the sample covariance matrix of the array received data, and respectively denote the actual steering vector and the presumed steering vector, is the orthogonal component of the mismatch vector . Here, this inequality constraint is used to prevent the corrected steering vector from converging to any interferer steering vector. The numerical solution of the above optimization formulation is available.
Substituting the estimated steering vector into the minimum variance distortionless response (MVDR) beamformer, the signal steering vector estimation-based MVDR beamformer is given as
VOCAL Technologies offers custom designed data-dependent adaptive beamforming solutions, with MVDR filters as a potential front end. Our custom implementations of such systems are meant to deliver optimum performance for your specific signal processing task. Contact us today to discuss your solution!