Advanced optimization algorithms for sensor arrays and multi-antenna communications

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorAbrudan, Traian
dc.contributor.departmentSignaalinkäsittelyn ja akustiikan laitosfi
dc.date.accessioned2012-08-21T07:42:12Z
dc.date.available2012-08-21T07:42:12Z
dc.date.issued2008
dc.description.abstractOptimization problems arise frequently in sensor array and multi-channel signal processing applications. Often, optimization needs to be performed subject to a matrix constraint. In particular, unitary matrices play a crucial role in communications and sensor array signal processing. They are involved in almost all modern multi-antenna transceiver techniques, as well as sensor array applications in biomedicine, machine learning and vision, astronomy and radars. In this thesis, algorithms for optimization under unitary matrix constraint stemming from Riemannian geometry are developed. Steepest descent (SD) and conjugate gradient (CG) algorithms operating on the Lie group of unitary matrices are derived. They have the ability to find the optimal solution in a numerically efficient manner and satisfy the constraint accurately. Novel line search methods specially tailored for this type of optimization are also introduced. The proposed approaches exploit the geometrical properties of the constraint space in order to reduce the computational complexity. Array and multi-channel signal processing techniques are key technologies in wireless communication systems. High capacity and link reliability may be achieved by using multiple transmit and receive antennas. Combining multi-antenna techniques with multicarrier transmission leads to high the spectral efficiency and helps to cope with severe multipath propagation. The problem of channel equalization in MIMO-OFDM systems is also addressed in this thesis. A blind algorithm that optimizes of a combined criterion in order to be cancel both inter-symbol and co-channel interference is proposed. The algorithm local converge properties are established as well.en
dc.format.extentVerkkokirja (997 KB, 95 s.)
dc.format.mimetypeapplication/pdf
dc.identifier.isbn978-951-22-9607-1
dc.identifier.isbn978-951-22-9606-4 (printed)#8195;
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/4546
dc.identifier.urnURN:ISBN:978-951-22-9607-1
dc.language.isoenen
dc.publisherTeknillinen korkeakouluen
dc.relation.haspart[Publication 1]: Traian E. Abrudan, Jan Eriksson, and Visa Koivunen. 2008. Steepest descent algorithms for optimization under unitary matrix constraint. IEEE Transactions on Signal Processing, volume 56, number 3, pages 1134-1147. © 2008 IEEE. By permission.en
dc.relation.haspart[Publication 2]: Traian Abrudan, Jan Eriksson, and Visa Koivunen. 2008. Conjugate gradient algorithm for optimization under unitary matrix constraint. Helsinki University of Technology, Department of Signal Processing and Acoustics, Report 4. ISBN 978-951-22-9483-1. ISSN 1797-4267. Submitted for publication. © 2008 by authors.en
dc.relation.haspart[Publication 3]: Traian Abrudan, Jan Eriksson, and Visa Koivunen. 2005. Optimization under unitary matrix constraint using approximate matrix exponential. In: Conference Record of the Thirty-Ninth Asilomar Conference on Signals, Systems and Computers (ACSSC 2005). Pacific Grove, CA, USA. 28 October - 1 November 2005, pages 242-246. © 2005 IEEE. By permission.en
dc.relation.haspart[Publication 4]: Traian Abrudan, Jan Eriksson, and Visa Koivunen. 2007. Efficient line search methods for Riemannian optimization under unitary matrix constraint. In: Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers (ACSSC 2007). Pacific Grove, CA, USA. 4-7 November 2007, pages 671-675. © 2007 IEEE. By permission.en
dc.relation.haspart[Publication 5]: Traian Abrudan, Jan Eriksson, and Visa Koivunen. 2008. Efficient Riemannian algorithms for optimization under unitary matrix constraint. In: Proceedings of the 33rd IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2008). Las Vegas, NV, USA. 31 March - 4 April 2008, pages 2353-2356. © 2008 IEEE. By permission.en
dc.relation.haspart[Publication 6]: Traian Abrudan, Marius Sirbu, and Visa Koivunen. 2003. Blind multi-user receiver for MIMO-OFDM systems. In: Proceedings of the 4th IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2003). Rome, Italy. 15-18 June 2003, pages 363-367. © 2003 IEEE. By permission.en
dc.relation.haspart[Publication 7]: Traian Emanuel Abrudan and Visa Koivunen. 2007. Blind equalization in spatial multiplexing MIMO-OFDM systems based on vector CMA and decorrelation criteria. Wireless Personal Communications, volume 43, number 4, pages 1151-1172.en
dc.relation.haspart[Errata file]: Errata of publications 1, 3, 5 and 7en
dc.subject.keywordoptimizationen
dc.subject.keywordunitary matrixen
dc.subject.keywordarray signal processingen
dc.subject.keywordblind separationen
dc.subject.keywordequalizationen
dc.subject.keywordMIMOen
dc.subject.keywordOFDMen
dc.subject.otherElectrical engineeringen
dc.titleAdvanced optimization algorithms for sensor arrays and multi-antenna communicationsen
dc.typeG5 Artikkeliväitöskirjafi
dc.type.dcmitypetexten
dc.type.ontasotVäitöskirja (artikkeli)fi
dc.type.ontasotDoctoral dissertation (article-based)en
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local.aalto.digifolderAalto_66928
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