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. |
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Copyright © The Author(s), 2015. Published by Science Publishing Group |
Software-Defined Radio, Sampling, Big Data, Market Paradigm, Agent-Based Detection, Wireless Networks
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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
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
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
@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} }
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 AU - Akinbode Alex Olawole Y1 - 2015/08/13 PY - 2015 N1 - https://doi.org/10.11648/j.cssp.20150403.11 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 SP - 18 EP - 22 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 ER -