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.
DISCLOSURE STATEMENT
No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
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Rekha R. S.
Rekha R S is a research scholar pursuing her PhD at the research center, Department of Electronics and Communication Engineering, Vemana Institute of Technology, Bengaluru, under VTU Part-time PhD in wireless communication systems. Email: [email protected]
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M. C. Parameshwara
M C Parameshwara obtained the BE degree from Bangalore University in electronics and communication engineering in 1999, MTech in electronics engineering from BMSCE, Bangalore, Visvesvaraya Technological University (VTU) in 2007 & obtained PhD in VLSI from VTU, Belagavi in 2018. He joined the Department of Electronics & Communication Engineering, Vemana Institute of Technology in 2004 as an assistant professor. Email: [email protected]
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Veerendra Dakulagi
Veerendra Dakulagi PhD, is an associate professor of the Electronics and Communication Engineering Department, at the Guru Nanak Dev Engineering College, Bidar, Karnataka, India, specialized in electromagnetics and array signal processing. Dr Dakulagi acquired PhD in array signal processing at the Visvesvaraya Technological University, Belagavi, India. After his doctoral studies, he worked as a postdoctoral fellow in electronics & communication engineering at UM, Malaysia. Dr Dakulagi's research is focused on signal processing and communications that include statistical and array signal processing, adaptive beamforming, spatial diversity in wireless communications, and multiuser and multi-input multi-output communications. He authored more than 40 research articles, edited a book, and 10 book chapters, and is a holder of 05 registered patent grants. He is the recipient of the INSA Visiting Scientist Award (2022), VGST Young Researcher Award (2021), and VGST Best Researcher Award (2017). Corresponding author. Email: [email protected]