Affiliation:
1. KITCOE ,Kolhapur, Maharashtra,Indi
Abstract
Adaptive signal processing sensor arrays, known also as smart antennas .The smart antenna adaptive algorithms achieve the best weight vector for beam forming by iterative means. The Least Mean Square (LMS) algorithm, is an adaptive algorithm .LMS incorporates an iterative procedure that makes successive corrections to the weight vector in the direction of the negative of the gradient vector which eventually leads to the minimum mean square error. Beam forming is directly determined by the two factors. The performance of the traditional LMS algorithm for different parameters is analysed in this paper. This algorithm can be applied to beam forming with the software Matlab. The result obtain can achieve faster convergence and lower steady state error. The algorithms can be simulated in MATLAB 7.10 version.
Publisher
North Atlantic University Union (NAUN)
Reference7 articles.
1. Shiann-Jeng Yu and Ju-Hong Lee,“Adaptive Array Beamforming Based on an Efficient Technique”, IEEE trans. Antennas and Propagation. 1996,44(8) 1094-1101.
2. L . S. Reed, J. D. Mallett, “Rapid Convergence Rate in Adaptive Arrays”, IEEE trans. Acoustics Aerospace and Electronic Systems. 1974, 10(6):853-863
3. Komal R. Borisagar and Dr. G.R.Kulkarni, “Simulation and Comparative Analysis of LMS and RLS Algorithms Using Real Time Speech Input Signal”,. Global Journal of Researches in Engineering Page 44 Vol.10 Issue 5 (Ver1.0)October2010.
4. Raymond G Kwang and Edward W.Johnston, “Variable Ste p Size LMS algorithm”, IEEE Trans.Signal Processing vol 40 No 7, July 1992.
5. Sidi Bahri and Fethi Bendimerad, “Performance of Adaptive Beamforming Algorithm f or LMS-MCCDMA MIMO Smart Antennas”, The International Arab Journal of Information Technology, Vol. 6, No. 3, July 2009.