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An Algorithm for a Sub-Nyquist Rate AM and FM Software-Defined Radio Based on the Market Paradigm

Received: 23 July 2015     Accepted: 5 August 2015     Published: 13 August 2015
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Abstract

Software-defined radio accomplishes both modulation and demodulation processes using software. While this has a number of advantages, which includes flexibility, interoperability, sustainability, and adaptability, the requirement for sampling the signal for digital processes toward adequate recovery often involves the use of a fast but expensive analogue-to-digital converter (ADC). This, in a way translates to higher cost and requirement for bigger storage. This paper presents a method of switched signal recovery at uniform sampling rates that are less than the frequently over-estimated Nyquist rate employed. In particular, an algorithm for achieving this was implemented for an AM wave, under-sampled at varied uniform rates up-to twice the carrier rate, and then demodulated using the Market Paradigm. Furthermore,the slope detectorwas also implemented by including a differentiator after the sampling stage of the algorithm. The simulated results showed that the algorithm was able to recover the message signal at sampling rates far less than twice the carrier rate without the need for any additional hardware. Specifically, the best value of the Spurious Free Dynamic Range (SFDR) obtained for the recovered message signal was 20dB at a sampling rate of less than 20% of the Nyquist rate for the carrier signal

Published in Science Journal of Circuits, Systems and Signal Processing (Volume 4, Issue 3)
DOI 10.11648/j.cssp.20150403.11
Page(s) 18-22
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), 2015. Published by Science Publishing Group

Keywords

Software-Defined Radio, Sampling, Big Data, Market Paradigm, Agent-Based Detection, Wireless Networks

References
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[3] Landau, H. J. (1967): “Necessary density conditions for sampling and interpolation of certain entire functions,” Acta Math., vol.117, pp. 37-52, Feb. 1967.
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[5] Lin, Y. P. and Vaidyanathan, P. P., “Periodically nonuniform sampling of bandpass signals,” IEEE Trans. Circuits Syst. II, vol. 45, no. 3, pp. 340-351, Mar. 1998
[6] Millhaem, M. (2006): “Software shapes next-generation RF instrumentation (radio frequency, software-defined radio)”. Wireless Design and Development Publication, Available Online:http://www.highbeam.com/doc/ 1G1- 155474366.html
[7] Mishali, M. and Eldar, Y.C. (2010): “From Theory to Practice: Sub-Nyquist Sampling of Sparse Wideband Analog Signals”, IEEE Journal of Selected Topics in Signal processing, Vol. 4, No. 2, pp. 375-390.
[8] Mishali, M. and Eldar, Y.C. (2011): Sub-Nyquist Sampling – Bridging theory and practice, IEEE Signal Processing Magazine, Vol. 28 No. 6, pp. 98 – 124.
[9] Mitola III, J. (1992): Software Radios- Survey, Critical Evaluation and Future Directions, In Telesystem Conference NTC-92, pp. 15-23.
[10] Otolorin, J.A. (2013): Development of an Algorithm for Implementing a Low Cost Frequency Modulated (FM) Receiver, Unpublished M.Sc. Thesis, Department of Electronic and Electrical Engineering, ObafemiAwolowo University, Ile-Ife, 101p.
[11] Olademeji, O. O. (2008): “Development of a New Algorithm for the Implementation of High Precision Delta-Sigma Digital-to-Analog Converter”, Unpublished M.Sc. Thesis, Department of Electronic and Electrical Engineering, ObafemiAwolowo University, Ile-Ife., pp. 64 - 73
[12] Proakis, J. G. and Manolakis, D. G. (1992): Digital Signal Processing: Principles, Algorithms, and Application. Macmillan, New York, pp. 395 – 467.
[13] Proakis, J.G. and Salehi, M. (1994): “Communication Systems Engineering”, Prentice-Hall International, Inc. New Jersey, pp 297, 328- 385.
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[15] Sharma, S. P. (2009): Basic Radio and Television,Tata McGraw-Hill, New Delhi, pp. 330-371
[16] ShajedulHasan, S.M., and Balister, P. (2005): “Prototyping a Software Defined Radio ReceiverBased on USRP and OSSIE ”, Chameleonic Radio Technical Memo No. 1, pp. 1, 8.
[17] Vaughan, R. G., Scott, N. L., and White, D. R. (1991): “The theory of bandpass sampling,” IEEE Trans. Signal Processing, vol. 39, No.9, pp. 1973-1984.
[18] Yesufu, O.A. and Yesufu, T.K. (2003): Development of the Market Paradigm for Analyzing Systems, Social Science Research Network (SSRN) Electronic Journals of Agriculture and Natural Resource Economics, Dispute & Conflict Resolution, Econometrics, Strategy & Economics, Development Economics, Risk Management, Environmental Economics, Available Online through http://www.ssrn.com/abstract=437181.
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  • APA Style

    Thomas KokumoYesufu, Joel Adeniyi Otolorin, Akinbode Alex Olawole. (2015). An Algorithm for a Sub-Nyquist Rate AM and FM Software-Defined Radio Based on the Market Paradigm. Science Journal of Circuits, Systems and Signal Processing, 4(3), 18-22. https://doi.org/10.11648/j.cssp.20150403.11

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    ACS Style

    Thomas KokumoYesufu; Joel Adeniyi Otolorin; Akinbode Alex Olawole. An Algorithm for a Sub-Nyquist Rate AM and FM Software-Defined Radio Based on the Market Paradigm. Sci. J. Circuits Syst. Signal Process. 2015, 4(3), 18-22. doi: 10.11648/j.cssp.20150403.11

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    AMA Style

    Thomas KokumoYesufu, Joel Adeniyi Otolorin, Akinbode Alex Olawole. An Algorithm for a Sub-Nyquist Rate AM and FM Software-Defined Radio Based on the Market Paradigm. Sci J Circuits Syst Signal Process. 2015;4(3):18-22. doi: 10.11648/j.cssp.20150403.11

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  • @article{10.11648/j.cssp.20150403.11,
      author = {Thomas KokumoYesufu and Joel Adeniyi Otolorin and Akinbode Alex Olawole},
      title = {An Algorithm for a Sub-Nyquist Rate AM and FM Software-Defined Radio Based on the Market Paradigm},
      journal = {Science Journal of Circuits, Systems and Signal Processing},
      volume = {4},
      number = {3},
      pages = {18-22},
      doi = {10.11648/j.cssp.20150403.11},
      url = {https://doi.org/10.11648/j.cssp.20150403.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cssp.20150403.11},
      abstract = {Software-defined radio accomplishes both modulation and demodulation processes using software. While this has a number of advantages, which includes flexibility, interoperability, sustainability, and adaptability, the requirement for sampling the signal for digital processes toward adequate recovery often involves the use of a fast but expensive analogue-to-digital converter (ADC). This, in a way translates to higher cost and requirement for bigger storage. This paper presents a method of switched signal recovery at uniform sampling rates that are less than the frequently over-estimated Nyquist rate employed. In particular, an algorithm for achieving this was implemented for an AM wave, under-sampled at varied uniform rates up-to twice the carrier rate, and then demodulated using the Market Paradigm. Furthermore,the slope detectorwas also implemented by including a differentiator after the sampling stage of the algorithm. The simulated results showed that the algorithm was able to recover the message signal at sampling rates far less than twice the carrier rate without the need for any additional hardware. Specifically, the best value of the Spurious Free Dynamic Range (SFDR) obtained for the recovered message signal was 20dB at a sampling rate of less than 20% of the Nyquist rate for the carrier signal},
     year = {2015}
    }
    

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  • TY  - JOUR
    T1  - An Algorithm for a Sub-Nyquist Rate AM and FM Software-Defined Radio Based on the Market Paradigm
    AU  - Thomas KokumoYesufu
    AU  - Joel Adeniyi Otolorin
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    DO  - 10.11648/j.cssp.20150403.11
    T2  - Science Journal of Circuits, Systems and Signal Processing
    JF  - Science Journal of Circuits, Systems and Signal Processing
    JO  - Science Journal of Circuits, Systems and Signal Processing
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    PB  - Science Publishing Group
    SN  - 2326-9073
    UR  - https://doi.org/10.11648/j.cssp.20150403.11
    AB  - Software-defined radio accomplishes both modulation and demodulation processes using software. While this has a number of advantages, which includes flexibility, interoperability, sustainability, and adaptability, the requirement for sampling the signal for digital processes toward adequate recovery often involves the use of a fast but expensive analogue-to-digital converter (ADC). This, in a way translates to higher cost and requirement for bigger storage. This paper presents a method of switched signal recovery at uniform sampling rates that are less than the frequently over-estimated Nyquist rate employed. In particular, an algorithm for achieving this was implemented for an AM wave, under-sampled at varied uniform rates up-to twice the carrier rate, and then demodulated using the Market Paradigm. Furthermore,the slope detectorwas also implemented by including a differentiator after the sampling stage of the algorithm. The simulated results showed that the algorithm was able to recover the message signal at sampling rates far less than twice the carrier rate without the need for any additional hardware. Specifically, the best value of the Spurious Free Dynamic Range (SFDR) obtained for the recovered message signal was 20dB at a sampling rate of less than 20% of the Nyquist rate for the carrier signal
    VL  - 4
    IS  - 3
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Author Information
  • Department of Electronic and Electrical Engineering,ObafemiAwolowo University, Ile-Ife, Nigeria

  • Department of Electronic and Electrical Engineering,ObafemiAwolowo University, Ile-Ife, Nigeria

  • Department of Electronic and Electrical Engineering,ObafemiAwolowo University, Ile-Ife, Nigeria

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