A novel digital beamforming technique based on homogeneous adaptation employing time-varying convergence factors

In this paper, a novel complex homogeneous adaptation least mean square algorithm (complex HA-LMS) for digital beamforming is presented. The proposed technique independently adjusts the real and imaginary components of the complex adaptive filter coefficients using optimally derived convergence factors. In addition, the convergence factors are updated at very sample iteration. The complex HA-LMS is applied to adaptive beamforming in a multi-antenna receiver processing Quadrature Amplitude Modulation (QAM) signals. Extensive simulation results show that the complex HA-LMS exhibits improved and consistent performance, in terms of the Symbol Error Rate (SER) and convergence speed, for different flat fading channel conditions and varied number of antenna elements, in contrast to the complex Least Mean Square algorithm (complex LMS) which uses a fixed convergence factor.