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Variable Step Size Normalized Least Mean Square Algorithm for Mobile Communication


Affiliations
1 Department of Electronics and Communication, Guru Nanak Dev Engineering College, Bidar, Karnataka, India
2 Department of Computer Science and Engineering, Guru Nanak Dev Engineering College, Bidar, Karnataka, India
 

This paper describes a robust variable step size normalized least mean square algorithm (VSSNLMSS) to enhance interference suppression in smart antenna system. The fixed step size normalized least mean square (NLMS) will result in a trade-off issue between convergence rate and steady-state mean square error (MSE) of NLMS algorithm. The purpose of a variable step-size normalized LMS algorithm is to solve the dilemma of fast convergence rate and low MSE. The proposed VSSNLMS algorithm reduces the MSE and shows faster convergence rate when compared to the conventional LMS and NLMS. Moreover, the enhanced performance of the new VSSNLMS algorithm is validated from the output beam pattern.

Keywords

Beamforming, LMS, MSE, NLMS, Smart Antenna, VSSNLMS.
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  • Variable Step Size Normalized Least Mean Square Algorithm for Mobile Communication

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Authors

Channveer Patil
Department of Electronics and Communication, Guru Nanak Dev Engineering College, Bidar, Karnataka, India
Durgesh Shastri
Department of Computer Science and Engineering, Guru Nanak Dev Engineering College, Bidar, Karnataka, India
Mahesh Hundekar
Department of Computer Science and Engineering, Guru Nanak Dev Engineering College, Bidar, Karnataka, India

Abstract


This paper describes a robust variable step size normalized least mean square algorithm (VSSNLMSS) to enhance interference suppression in smart antenna system. The fixed step size normalized least mean square (NLMS) will result in a trade-off issue between convergence rate and steady-state mean square error (MSE) of NLMS algorithm. The purpose of a variable step-size normalized LMS algorithm is to solve the dilemma of fast convergence rate and low MSE. The proposed VSSNLMS algorithm reduces the MSE and shows faster convergence rate when compared to the conventional LMS and NLMS. Moreover, the enhanced performance of the new VSSNLMS algorithm is validated from the output beam pattern.

Keywords


Beamforming, LMS, MSE, NLMS, Smart Antenna, VSSNLMS.

References