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A Robust Least Mean Square Algorithm for Adaptive Array Signal Processing

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Abstract

Least Mean Square (LMS) has been the most popular scheme in the realization of adaptive beamforming algorithms. In this paper a Robust Least Mean Square (R-LMS) algorithm is proposed which uses ratio parameters to control the contribution of product vectors in the weight upgrading process. The idea behind the proposed scheme is inclusion of previous information in place of relying solely on current sample. The performance enhancement by R-LMS algorithm is achieved with insignificant increase in computational complexity of LMS algorithm, so the crux of the conventional technique is not lost. Simulation results are also presented which illustrate that R-LMS provides relatively fast convergence, less Brownian motion and improved stability.

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Authors and Affiliations

  1. COMSATS Institute of Information Technology, Park Road, Chak Shahzad, Islamabad, Pakistan

    Rana Liaqat Ali, Shahid A. Khan, Anum Ali,  Anis-ur-Rehman & Shahzad A. Malik

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  1. Rana Liaqat Ali
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  2. Shahid A. Khan
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  3. Anum Ali
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  4. Anis-ur-Rehman
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  5. Shahzad A. Malik
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Correspondence to Rana Liaqat Ali.

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Ali, R.L., Khan, S.A., Ali, A. et al. A Robust Least Mean Square Algorithm for Adaptive Array Signal Processing. Wireless Pers Commun 68, 1449–1461 (2013). https://doi.org/10.1007/s11277-012-0533-6

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  • DOI: https://doi.org/10.1007/s11277-012-0533-6

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