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Implementation Aspects in DFT Modulated Filter Bank Transceivers for Cognitive Radio

Received: 12 September 2014     Accepted: 4 November 2014     Published: 18 November 2014
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Abstract

Discrete Fourier transform (DFT) modulated filter banks (FBs) are considered as strong tools used to implement both dynamic spectrum access and spectrum sensing in cognitive radio (CR) systems. High time-frequency (TF) resolution for spectral estimation and effective spectrum access with low complexity transceivers are the basic objectives in CR systems. However, the limitations of self-interference in DFT FBs as well as a primary user interference increase the overall transceiver complexity. In this paper, we design DFT modulated FBs which take into account the aforementioned contradicting requirements of high resolution capabilities, efficient spectrum access and affordable implementation effort for an additive white Gaussian channel. Four simple designs are presented and their performance are investigated and compared for a CR system with basic transmission parameters resembling those of IEEE 802.11g.

Published in International Journal of Wireless Communications and Mobile Computing (Volume 2, Issue 4-1)

This article belongs to the Special Issue 5G Wireless Communication Systems

DOI 10.11648/j.wcmc.s.2014020401.11
Page(s) 1-10
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2014. Published by Science Publishing Group

Keywords

Cognitive Radio, Filter Banks, Spectrum Access, Spectrum Sensing, Intersymbol Interference, Gabor System

References
[1] E. Biglieri, A. J. Goldsmith, L. J. Greenstein, N. B. Mandayam, and H. V. Poor, Principles of cognitive radio. Cambridge University press: Cambridge University Press, New York, 2013.
[2] W.-B. Chien, C.-K. Yang, and Y.-H. Huang, “Energy-saving cooperative spectrum sensing processor for cognitive radio system,” circuits and systems I: Regular Papers, IEEE Transactions on, vol. 58, no. 4, pp. 711–723, April 2011.
[3] D. Joshi, D. Popescu, and O. Dobre, “Adaptive spectrum sensing with noise variance estimation for dynamic cognitive radio systems,” in Information Sciences and Systems (CISS), 2010 44th Annual Conference on, March 2010, pp. 1–5.
[4] H. Bölcskei, F. Hlawatsch, and H. G. Feichtinger, “Equivalence of DFT filter banks and Gabor expansions,” in Proc. of SPIE: wavelet applications in signal and image processing III, vol. 2569, July 1995, pp. 128–139.
[5] H. Feichtinger and T. Strohmer, Gabor analysis and algorithms: theory and applications, ser. Applied and numerical harmonic analysis. Birkhäuser Verlag GmbH, 2012.
[6] T. Hunziker, U. Rehman, and D. Dahlhaus, “Spectrum sensing in cognitive radios: Design of DFT filter banks achieving maximal time frequency resolution,” in 8th International Conference on Information, Communications and Signal Processing (ICICS) 2011, Dec 2011, pp. 1–5.
[7] Z. Ju, T. Hunziker, and D. Dahlhaus, “Optimized paraunitary filter banks for time-frequency channel diagonalization,” in EURASIP journal on advances in signal processing, vol. 2010, Dec. 2010.
[8] N. Mansour and D. Dahlhaus, “Interference in DFT modulated filter bank transceivers for cognitive radio,” in European Wireless 2014; 20th European Wireless Conference; Proceedings of, May 2014, pp. 1–7.
[9] J. Proakis, Digital communications. McGraw Hill, New York, 4th ed., 2000.
[10] P.P. Vaidyanathan, Multirate systems and filter banks. Prentice Hall Signal Processing Series, New Jersey, 1993.
[11] B. Boashash, “Time-frequency signal analysis and processing,” Queensland university, Brisbane, Australia.
[12] S. Boyd and L. Vandenberghe, Convex optimization. Cambridge UK: Cambridge University Press, New York, 2004.
[13] P. Gill, W. Murray, and M. Saunders, “SNOPT: An SQP algorithm for large-scale constrained optimization,” SIAM Journal on Optimization, vol. 12, no. 4, pp. 979–1006, 2002.
[14] N.J. Fliege, Multirate Digital Signal Processing: Multirate systems, filter banks, wavelets, John Wiley & Sons, Chichester, 1994.
[15] S. Verdu, Multiuser detection. Cambridge University Press: Press Syndicate of the University of Cambridge, 1998.
[16] T. Hunziker, Z. Ju, and D. Dahlhaus, “Time-frequency channel parameterization with application to multi-mode receivers,” IEICE Trans. Commun., pp. 3717–3725, Dec 2009.
Cite This Article
  • APA Style

    Nour Mansour, Dirk Dahlhaus. (2014). Implementation Aspects in DFT Modulated Filter Bank Transceivers for Cognitive Radio. International Journal of Wireless Communications and Mobile Computing, 2(4-1), 1-10. https://doi.org/10.11648/j.wcmc.s.2014020401.11

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    ACS Style

    Nour Mansour; Dirk Dahlhaus. Implementation Aspects in DFT Modulated Filter Bank Transceivers for Cognitive Radio. Int. J. Wirel. Commun. Mobile Comput. 2014, 2(4-1), 1-10. doi: 10.11648/j.wcmc.s.2014020401.11

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    AMA Style

    Nour Mansour, Dirk Dahlhaus. Implementation Aspects in DFT Modulated Filter Bank Transceivers for Cognitive Radio. Int J Wirel Commun Mobile Comput. 2014;2(4-1):1-10. doi: 10.11648/j.wcmc.s.2014020401.11

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  • @article{10.11648/j.wcmc.s.2014020401.11,
      author = {Nour Mansour and Dirk Dahlhaus},
      title = {Implementation Aspects in DFT Modulated Filter Bank Transceivers for Cognitive Radio},
      journal = {International Journal of Wireless Communications and Mobile Computing},
      volume = {2},
      number = {4-1},
      pages = {1-10},
      doi = {10.11648/j.wcmc.s.2014020401.11},
      url = {https://doi.org/10.11648/j.wcmc.s.2014020401.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wcmc.s.2014020401.11},
      abstract = {Discrete Fourier transform (DFT) modulated filter banks (FBs) are considered as strong tools used to implement both dynamic spectrum access and spectrum sensing in cognitive radio (CR) systems. High time-frequency (TF) resolution for spectral estimation and effective spectrum access with low complexity transceivers are the basic objectives in CR systems. However, the limitations of self-interference in DFT FBs as well as a primary user interference increase the overall transceiver complexity. In this paper, we design DFT modulated FBs which take into account the aforementioned contradicting requirements of high resolution capabilities, efficient spectrum access and affordable implementation effort for an additive white Gaussian channel. Four simple designs are presented and their performance are investigated and compared for a CR system with basic transmission parameters resembling those of IEEE 802.11g.},
     year = {2014}
    }
    

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    AB  - Discrete Fourier transform (DFT) modulated filter banks (FBs) are considered as strong tools used to implement both dynamic spectrum access and spectrum sensing in cognitive radio (CR) systems. High time-frequency (TF) resolution for spectral estimation and effective spectrum access with low complexity transceivers are the basic objectives in CR systems. However, the limitations of self-interference in DFT FBs as well as a primary user interference increase the overall transceiver complexity. In this paper, we design DFT modulated FBs which take into account the aforementioned contradicting requirements of high resolution capabilities, efficient spectrum access and affordable implementation effort for an additive white Gaussian channel. Four simple designs are presented and their performance are investigated and compared for a CR system with basic transmission parameters resembling those of IEEE 802.11g.
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Author Information
  • Communications Laboratory, University of Kassel, Kassel, Germany

  • Communications Laboratory, University of Kassel, Kassel, Germany

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