A class of constant modulus algorithms for uniform linear arrays with a conjugate symmetric constraint
A class of constant modulus algorithms (CMAs) subject to a conjugate symmetric constraint is proposed for blind beamforming based on the uniform linear array structure. The constraint is derived from the beamformer with an optimum output signal-to-interference-plus-noise ratio (SINR). The effect of...
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| Published in | Signal processing Vol. 90; no. 9; pp. 2760 - 2765 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Amsterdam
Elsevier B.V
01.09.2010
Elsevier |
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| Online Access | Get full text |
| ISSN | 0165-1684 1872-7557 |
| DOI | 10.1016/j.sigpro.2010.04.003 |
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| Abstract | A class of constant modulus algorithms (CMAs) subject to a conjugate symmetric constraint is proposed for blind beamforming based on the uniform linear array structure. The constraint is derived from the beamformer with an optimum output signal-to-interference-plus-noise ratio (SINR). The effect of the additional constraint is equivalent to adding a second step to the original adaptive algorithms. The proposed approach is general and can be applied to both the traditional CMA and its all kinds of variants, such as the linearly constrained CMA (LCCMA) and the least squares CMA (LSCMA) as two examples. With this constraint, the modified CMAs will always generate a weight vector in the desired form for each update and the number of adaptive variables is effectively reduced by half, leading to a much improved overall performance. |
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| AbstractList | A class of constant modulus algorithms (CMAs) subject to a conjugate symmetric constraint is proposed for blind beamforming based on the uniform linear array structure. The constraint is derived from the beamformer with an optimum output signal-to-interference-plus-noise ratio (SINR). The effect of the additional constraint is equivalent to adding a second step to the original adaptive algorithms. The proposed approach is general and can be applied to both the traditional CMA and its all kinds of variants, such as the linearly constrained CMA (LCCMA) and the least squares CMA (LSCMA) as two examples. With this constraint, the modified CMAs will always generate a weight vector in the desired form for each update and the number of adaptive variables is effectively reduced by half, leading to a much improved overall performance. |
| Author | Liu, Wei Langley, Richard J. Zhang, Lei |
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| Cites_doi | 10.1109/ICASSP.1986.1168686 10.1109/TSP.2008.921721 10.1109/TSP.2008.2005861 10.1109/TSP.2004.840781 10.1109/26.837051 10.1109/4234.709436 10.1109/8.86911 10.1109/TSP.2004.826167 10.1109/5.720246 10.1109/5.622504 10.1109/ICASSP.2008.4518179 10.1109/79.526899 10.1109/TSP.2007.913161 10.1109/LCOMM.2005.04022 10.1109/TSP.2006.873651 10.1016/j.sigpro.2007.04.007 10.1109/18.391241 |
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| Keywords | Blind beamforming Conjugate symmetric Constant modulus Uniform linear arrays Performance evaluation Adaptive algorithm Updating Output signal Beam forming Constant modulus algorithm Least squares method Linear antenna arrays Signal to interference plus noise ratio |
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| SubjectTerms | Algorithms Applied sciences Blind beamforming Conjugate symmetric Conjugates Constant modulus Detection, estimation, filtering, equalization, prediction Equivalence Exact sciences and technology Information, signal and communications theory Least squares method Linear arrays Mathematical analysis Optimization Signal and communications theory Signal, noise Telecommunications and information theory Uniform linear arrays Weight reduction |
| Title | A class of constant modulus algorithms for uniform linear arrays with a conjugate symmetric constraint |
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