Performance enhancement of adaptive beamforming algorithms based on a combination method

This paper proposes new two adaptive beamforming algorithms based on a combined method. The first proposal combination method includes merging pure Conjugate Gradient Method (CGM) with pure Normalized Least Mean Square (NLMS) algorithms, so that the first a new algorithm is called as CGM-NLMS. While the second proposed algorithm merges pure CGM with a Modified NLMS algorithm (MNLMS). The MNLMS algorithm is regarded as a variable regularization parameter that is fixed in the conventional NLMS algorithm. Then the new combination algorithm is called as CGM-MNLMS algorithm. Through simulation results of adaptive beamforming system using an Additive White Gaussian Noise (AWGN) channel model, the two new proposed algorithms provides fast convergence time, higher interference suppression capability and low level of MSD, and MSE at steady state compared with the pure CGM and pure NLMS algorithms.