Applications of fast QR-decomposition based adaptive algorithms in wireless systems

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en Mohammad, Mohammed Mobien 2017-05-26T09:01:57Z 2017-05-26T09:01:57Z 2017
dc.identifier.isbn 978-952-60-7457-3 (electronic)
dc.identifier.isbn 978-952-60-7458-0 (printed)
dc.identifier.issn 1799-4942 (electronic)
dc.identifier.issn 1799-4934 (printed)
dc.identifier.issn 1799-4934 (ISSN-L)
dc.description.abstract This thesis presents four contributions: first, it develops new techniques to extend the range of applications of computationally efficient (comparing to recursive least-squares (RLS) algorithm) fast QR-decomposition least-squares (FQRD-LS) algorithms; second, it develops new version of FQRD-LS algorithm for widely-linear (WL) input signal; third, It presents fixed-point analysis of FQRD-LS algorithm; and finally, it applies contant modulus algorithm (CMA) framework to the inverse QR-decomposition recursive least-squares (QRD-RLS) algorithm.  The main idea in the new techniques is to make available the adaptive filter coefficients using the internal variables of the FQRD-RLS algorithm. Four applications that result from using these techniques are: system identification, burst-trained equalization, broad-band beamformation, and predistortion.  WL adaptive algorithms are well suited for non-circular input signals, which arises for example in adaptive beamforming scenario when number of sources is greater than the number of antennas. In fixed point analysis of FQRD-LS algorithm we present: mathematical expressions for the mean square quantization error (MSQE) of all internal variables of the FQRD-LS algorithms; and derive the conditions that guarantee the stability of FQRD-LS algorithms for the purpose of fixed-point implementation. Finally, we show how to apply the CMA framework toward inverse QRD-RLS algorithm. We show application of CMA based IQRD-RLS algorithm in blind equalization of an optical channel. en
dc.format.extent 151 + app. 85
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher Aalto University en
dc.publisher Aalto-yliopisto fi
dc.relation.ispartofseries Aalto University publication series DOCTORAL DISSERTATIONS en
dc.relation.ispartofseries 102/2017
dc.relation.haspart [Publication 1]: M. Shoaib, S. Werner, and J. A. Apolinario Jr. Reduced complexity solution for weight extraction in QRD-LSL algorithm. IEEE Signal Processing Letters, Vol. 15, pages 277–280, Feb 2008. DOI: 10.1109/LSP.2008.917023
dc.relation.haspart [Publication 2]: M. Shoaib, S. Werner, and J. A. Apolinario Jr. Multichannel Fast QR-Decomposition Algorithms: Weight Extraction Method and its Applications. IEEE Transactions on Signal Processing, Vol. 58, Issue 1, pages 175–188, Jan 2010. DOI: 10.1109/TSP.2009.2030594
dc.relation.haspart [Publication 3]: M. Shoaib, and S. Alshebeili. Fixed-Point Implementation of Fast QR-Decomposition Recursive Least-Squares Algorithms (FQRD-RLS): Stability Conditions and Quantization Errors Analysis. Circuits, Systems, and Signal Processing, Vol. 32, Issue 4, pages 1551-1574, Jan 2013. DOI: 10.1007/s00034-012-9526-7
dc.relation.haspart [Publication 4]: A.M. Ragheb, M. Shoaib, S. Alshebeili, H. Fathallah. Enhanced Blind Equalization for Optical DP-QAM in Finite Precision Hardware. IEEE Photonics Technology Letters, Vol. 27, Issue 2, pages 181–184, Jan 2015. DOI: 10.1109/LPT.2014.2364265
dc.relation.haspart [Publication 5]: M. Shoaib, S. Werner, J. A. Apolinario Jr., and T. I. Laakso. Solution to the weight extraction problem in Fast QR-decomposition RLS algorithms. In International Conference on Acoustics, Speech, and Signal Processing, Toulouse, France, May 2006. DOI: 10.1109/ICASSP.2006.1660718
dc.relation.haspart [Publication 6]: M. Shoaib, S.Werner, J. A. Apolinario Jr., and T. I. Laakso. Equivalent Output-Filtering using Fast QRD-RLS Algorithm for Burst-Type Training Applications. In International Symposium on Circuits and Systems, Kos, Greece, May 2006. DOI: 10.1109/ISCAS.2006.1692540
dc.relation.haspart [Publication 7]: M. Shoaib, S. Werner, J. A. Apolinario Jr., and T. I. Laakso. Multichannel fast QR-decomposition RLS algorithms with explicit weight extraction. In European Signal Processing Conference, Florence, Italy, May 2006.
dc.relation.haspart [Publication 8]: M. Shoaib, and S. Alshebeili. A fastwidely-linear QR-decomposition least-squares (FWL-QRD-RLS) algorithm. In International Conference on Acoustics, Speech, and Signal Processing, Vancouver, Canada, May 2013. DOI: 10.1109/ICASSP.2013.6638444
dc.subject.other Electrical engineering en
dc.subject.other Mathematics en
dc.title Applications of fast QR-decomposition based adaptive algorithms in wireless systems en
dc.type G5 Artikkeliväitöskirja fi Sähkötekniikan korkeakoulu fi School of Electrical Engineering en
dc.contributor.department Signaalinkäsittelyn ja akustiikan laitos fi
dc.contributor.department Department of Signal Processing and Acoustics en
dc.subject.keyword adaptive filters en
dc.subject.keyword least-squares en
dc.subject.keyword fast algorithms en
dc.subject.keyword weight extraction en
dc.subject.keyword fixed-point analysis en
dc.subject.keyword system identification en
dc.subject.keyword digital beam forming en
dc.subject.keyword pre-distortion en
dc.subject.keyword channel equalization en
dc.identifier.urn URN:ISBN:978-952-60-7457-3
dc.type.dcmitype text en
dc.type.ontasot Doctoral dissertation (article-based) en
dc.type.ontasot Väitöskirja (artikkeli) fi
dc.contributor.supervisor Wichman, Risto, Prof., Aalto University, Department of Signal Processing and Acoustics, Finland
dc.opn Tabus, Ioan, Tampere University of Technology, Finland
dc.rev Albu, Felix, Prof., Valahia University of Targoviste, Romania
dc.rev Rembold Petraglia, Mariane, Prof., Federal University of Rio de Janerio, Brazil 2017-06-13

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