Abstract
The least mean square (LMS) beamformer is an extensively considered method in numerous mobile communication applications principally because of its computational efficiency, dynamic tracking ability, and accurate adaptive beamforming. However, this method requires huge iterations to reduce the mean square error (MSE) to zero for successful adaptive beamforming. To overcome this, we use a speeding unit (SU) device to speed up the rate of convergence of the LMS beamformer. The proposed method is named as the improved LMS (ILMS) method which provides accurate adaptive beamforming in six to seven iterations. Furthermore, we improve the proposed LMS method by applying Hanning, Hamming, and Kaiser Windows to notably curb the peak side lobe levels (PSLL). These methods are named HN-ILMS, HM-ILMS, and KB-ILMS respectively. Experimental results show that proposed HN-ILMS, HM-ILMS, and KB-ILMS give accurate adaptive beamforming with reduced PSLL.
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