Adaptive array beamforming under Rayleigh fading environment

Beamforming is a signal processing technique used for directional signal transmission or reception. Without moving the individual elements of the antenna array physically, the array pattern can be steered in particular direction by adjusting the amplitude and phase, called weights of the signal. Several signal processing techniques are used to adjust the weights, which demonstrate the self steering capability of adaptive antenna array. But those techniques exhibit a trade off between the convergence rate and the mean square error. This paper explains a novel adaptive technique, called dual stage least mean square algorithm, which is able to track the desired signal amid the interfering signals and noise, even for low input signal-to-noise ratio (SNR). The simulation results show that the performance of dual stage LMS algorithm is better in terms of convergence, mean square error, error vector magnitude than the earlier least mean square (LMS) technique. These techniques are compared and verified using MATLAB.