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

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School of Electrical Engineering | Doctoral thesis (article-based) | Defence date: 2017-06-13
Degree programme
151 + app. 85
Aalto University publication series DOCTORAL DISSERTATIONS, 102/2017
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.
Supervising professor
Wichman, Risto, Prof., Aalto University, Department of Signal Processing and Acoustics, Finland
adaptive filters, least-squares, fast algorithms, weight extraction, fixed-point analysis, system identification, digital beam forming, pre-distortion, channel equalization
Other note
  • [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 View at publisher
  • [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 View at publisher
  • [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 View at publisher
  • [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 View at publisher
  • [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 View at publisher
  • [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 View at publisher
  • [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.
  • [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 View at publisher