Robust Auxiliary Vector Filtering with Constrained Constant Modulus Design for Beamforming

TL;DR

This paper introduces a robust auxiliary vector filtering algorithm based on a constrained constant modulus design, enhancing adaptive beamforming performance and convergence speed in large-array scenarios.

Contribution

It presents a novel AVF algorithm that decomposes the filter into constrained and unconstrained parts, improving robustness and convergence in adaptive beamforming.

Findings

Fast convergence demonstrated in simulations

Improved steady-state performance over existing methods

Robustness in various scenarios

Abstract

This paper proposes an auxiliary vector filtering (AVF) algorithm based on a constrained constant modulus (CCM) design for robust adaptive beamforming. This scheme provides an efficient way to deal with filters with a large number of elements. The proposed beamformer decomposes the adaptive filter into a constrained (reference vector filters) and an unconstrained (auxiliary vector filters) components. The weight vector is iterated by subtracting the scaling auxiliary vector from the reference vector. The scalar factor and the auxiliary vector depend on each other and are jointly calculated according to the CCM criterion. The proposed robust AVF algorithm provides an iterative exchange of information between the scalar factor and the auxiliary vector and thus leads to a fast convergence and an improved steady-state performance over the existing techniques. Simulations are performed to show the performance and the robustness of the proposed scheme and algorithm in several scenarios.