Optimization of Normalized Least Mean Square Algorithm of Smart Antenna Beamforming for Interference Mitigation

Abstract

A smart antenna is an array of antennas with signal processing capabilities to transmit/receive information in an adaptive manner. This capability continues to be investigated to find the best adaptive algorithm for the desired beamforming capability. This paper aims to provide a study and analysis of the effect of the normalized least mean square (NLMS) algorithm on step size parameter settings which have an impact on the desired minimum square error (MSE) value and on the nulling beam radiation pattern arrangement of smart antennas in its role in mitigating interference. The simulation for beamformer performance for 1000 iterations was carried out using the Matlab tool on the additional white noise gaussian (AWGN) channel and the simulation parameters were changed to some step size values (μ) with the NLMS algorithm for 16 antenna elements. The effect of the value of the step size μ is seen in the iterations number that takes place before the minimum error noise is obtained, where the increase in the value of this step size reduces the iterations number required; at the same time further improving MSE levels. From the pattern of amplitude response after the beamforming process, the result is an escalation in the number of nulling to increase the distance between the spaced elements taken. The interference source is eliminated/closed by placing the nulls in the path of the interference source where the worst interference level is obtained around -90 dB when the smallest step size is taken.