Low-Complexity Variable Forgetting Factor Constrained Constant Modulus RLS Algorithm for Adaptive Beamforming

TL;DR

This paper introduces a low-complexity RLS-based blind adaptive beamforming algorithm with a novel variable forgetting factor mechanism, improving learning and tracking performance under the CCM criterion.

Contribution

It proposes a new VFF mechanism integrated into a CCM-based RLS algorithm for adaptive beamforming, with detailed analysis and superior performance.

Findings

VFF mechanism enhances learning and tracking.

Algorithm outperforms existing VFF methods.

Steady-state MSE is improved.

Abstract

In this paper, a recursive least squares (RLS) based blind adaptive beamforming algorithm that features a new variable forgetting factor (VFF) mechanism is presented. The beamformer is designed according to the constrained constant modulus (CCM) criterion, and the proposed adaptive algorithm operates in the generalized sidelobe canceler (GSC) structure. A detailed study of its operating properties is carried out, including a convexity analysis and a mean squared error (MSE) analysis of its steady-state behavior. The results of numerical experiments demonstrate that the proposed VFF mechanism achieves a superior learning and tracking performance compared to other VFF mechanisms.