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Adaptive Arrays are currently the subject of extensive research, for improving the quality of the receiving signals in the presence of interfering signals in wireless communications. In this paper beamforming is performed considering a digital system using Least Mean Squares algorithm. The main emphasis is to discuss the effects of the weight approximation procedures on the overall performance of the LMS algorithm and the Beamforming. The same results can be obtained for other adaptive beamforming algorithms and their various modifications available in the literature. In this paper Least Mean Squares Algorithm has been used to show the effects of weight approximation methods. Weight approximation methods are used to convert the continuous valued weights into discrete valued weights which can be used by digital systems for beamforming. Two algorithms have been proposed for weight approximation. Their performance has been compared with the conventional methods. Comparisons have been made for Beampattern, Sidelobe level, Convergence rate, Stability. The proposed algorithms have been observed to give overall better results for slight increase in the computational cost. The effect of the convergence coefficient μ on the sidelobe levels of beampattern has also been discussed.

Effects of Weight Approximation Methods on Performance of Digital Beamforming Using Least Mean Squares Algorithm