Performance of Beamforming for Smart Antenna using Traditional LMS Algorithm for Various Parameters
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 succes...
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| Published in | International journal of computers and communications Vol. 15; pp. 8 - 13 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
14.04.2021
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| Online Access | Get full text |
| ISSN | 2074-1294 2074-1294 |
| DOI | 10.46300/91013.2021.15.2 |
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| Summary: | 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. |
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| ISSN: | 2074-1294 2074-1294 |
| DOI: | 10.46300/91013.2021.15.2 |