Blind Adaptive Constrained Constant-Modulus Reduced-Rank Interference Suppression Algorithms Based on Interpolation and Switched Decimation
This work proposes a blind adaptive reduced-rank scheme and constrained constant-modulus (CCM) adaptive algorithms for interference suppression in wireless communications systems. The proposed scheme and algorithms are based on a two-stage processing framework that consists of a transformation matri...
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| Published in: | IEEE transactions on signal processing Vol. 59; no. 2; pp. 681 - 695 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
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New York, NY
IEEE
01.02.2011
Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 1053-587X, 1941-0476 |
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| Abstract | This work proposes a blind adaptive reduced-rank scheme and constrained constant-modulus (CCM) adaptive algorithms for interference suppression in wireless communications systems. The proposed scheme and algorithms are based on a two-stage processing framework that consists of a transformation matrix that performs dimensionality reduction followed by a reduced-rank estimator. The complex structure of the transformation matrix of existing methods motivates the development of a blind adaptive reduced-rank constrained (BARC) scheme along with a low-complexity reduced-rank decomposition. The proposed BARC scheme and a reduced-rank decomposition based on the concept of joint interpolation, switched decimation and reduced-rank estimation subject to a set of constraints are then detailed. The proposed set of constraints ensures that the multipath components of the channel are combined prior to dimensionality reduction. We develop low-complexity joint interpolation and decimation techniques, stochastic gradient, and recursive least squares reduced-rank estimation algorithms. A model-order selection algorithm for adjusting the length of the estimators is devised along with techniques for determining the required number of switching branches to attain a predefined performance. An analysis of the convergence properties and issues of the proposed optimization and algorithms is carried out, and the key features of the optimization problem are discussed. We consider the application of the proposed algorithms to interference suppression in DS-CDMA systems. The results show that the proposed algorithms outperform the best known reduced-rank schemes, while requiring lower complexity. |
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| AbstractList | This work proposes a blind adaptive reduced-rank scheme and constrained constant-modulus (CCM) adaptive algorithms for interference suppression in wireless communications systems. The proposed scheme and algorithms are based on a two-stage processing framework that consists of a transformation matrix that performs dimensionality reduction followed by a reduced-rank estimator. The complex structure of the transformation matrix of existing methods motivates the development of a blind adaptive reduced-rank constrained (BARC) scheme along with a low-complexity reduced-rank decomposition. The proposed BARC scheme and a reduced-rank decomposition based on the concept of joint interpolation, switched decimation and reduced-rank estimation subject to a set of constraints are then detailed. The proposed set of constraints ensures that the multipath components of the channel are combined prior to dimensionality reduction. We develop low-complexity joint interpolation and decimation techniques, stochastic gradient, and recursive least squares reduced-rank estimation algorithms. A model-order selection algorithm for adjusting the length of the estimators is devised along with techniques for determining the required number of switching branches to attain a predefined performance. An analysis of the convergence properties and issues of the proposed optimization and algorithms is carried out, and the key features of the optimization problem are discussed. We consider the application of the proposed algorithms to interference suppression in DS-CDMA systems. The results show that the proposed algorithms outperform the best known reduced-rank schemes, while requiring lower complexity. |
| Author | de Lamare, R C Sampaio-Neto, R Haardt, M |
| Author_xml | – sequence: 1 givenname: R C surname: de Lamare fullname: de Lamare, R C email: rcd1500@ohm.york.ac.uk organization: Dept. of Electron., Univ. of York, York, UK – sequence: 2 givenname: R surname: Sampaio-Neto fullname: Sampaio-Neto, R email: raimundo@cetuc.puc-rio.br organization: CETUC, PUC-RIO, Rio de Janeiro, Brazil – sequence: 3 givenname: M surname: Haardt fullname: Haardt, M email: Martin.Haardt@tu-il-menau.de organization: Commun. Res. Lab., Ilmenau Univ. of Technol., Ilmenau, Germany |
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| Keywords | Performance evaluation Rank statistic iterative methods Adaptive algorithm Blind adaptive estimation Wireless telecommunication Adaptive estimation Stochastic method Adaptive method Optimization Least squares method Direct sequence Multistage method Model selection Blind identification Interference suppression Interpolation Dimension reduction Telecommunication system Code division multiple access Recursive method Signal processing spread spectrum systems Matrix method Decimation reduced-rank techniques |
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| SubjectTerms | Adaptive algorithms Algorithm design and analysis Algorithms Applied sciences Blind adaptive estimation Blinds Complexity theory Constraints Detection, estimation, filtering, equalization, prediction Estimation Exact sciences and technology Information, signal and communications theory Interference Interference suppression Interpolation iterative methods Miscellaneous Optimization reduced-rank techniques Reduction Signal and communications theory Signal processing Signal, noise spread spectrum systems Studies Switches Telecommunications and information theory Transformations Wireless communication Wireless communications |
| Title | Blind Adaptive Constrained Constant-Modulus Reduced-Rank Interference Suppression Algorithms Based on Interpolation and Switched Decimation |
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