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Modified LMS Beamformer for Interference Rejection

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Abstract

The classical least mean square (LMS) adaptive beamformer is one of the most widespread methods for producing a higher gain in the user direction and a lower gain in the directions of interferences. However, this method requires gradient estimation to update the complex antenna array weights. Thus, they do not use the previously available array samples for the required gradient estimation. Also, this method requires enormous iterations to minimize the error between the user signal and the desired signal. This aspect hinders the use of the classical LMS method in real-time systems where fast adaptive beamforming (ABF) and maximization of signal-to-interference (SIR) ratio are required. In this paper, the modified LMS beamformer is proposed which estimates the gradient by exploiting all the accessible samples. Furthermore, a double-crossed uniform linear array (ULA) called DCULA is presented. The proposed method is applied to this new configuration to enhance the interference rejection capability of the modified LMS ABF method.

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Correspondence to R. S. Rekha.

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Rekha, R.S., Parameshwara, M.C. & Dakulagi, V. Modified LMS Beamformer for Interference Rejection. Wireless Pers Commun 129, 2199–2211 (2023). https://doi.org/10.1007/s11277-023-10232-7

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