Sensing-Throughput Tradeoff for Cognitive Radio Systems with Unknown Received Power

  • Ankit Kaushik
  • Shree Krishna Sharma
  • Symeon Chatzinotas
  • Björn Ottersten
  • Friedrich Jondral
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 156)

Abstract

Understanding the performance of the cognitive radio systems is of great interest. Different paradigms have been extensively analyzed in the literature to perform secondary access to the licensed spectrum. Of these, Interweave System (IS) has been widely investigated for performance analysis. According to IS, sensing is employed at the Secondary Transmitter (ST) that protects the Primary Receiver (PR) from the interference induced. Thus, in order to control the interference at the PR, it is required to sustain a certain level of probability of detection. In this regard, the ST requires the knowledge of the received power. However, in practice, this knowledge is not available at the ST. Thereby performing analysis considering the prior knowledge of the received power is too idealistic, thus, do not depict the actual performance of the IS. Motivated by this fact, an estimation model that includes received power estimation is proposed. Considering a sensing-throughput tradeoff, we apply this model to characterize the performance of the IS. Most importantly, the proposed model captures the estimation error to determine the distortion in the system performance. Based on analysis, it is illustrated that the ideal model overestimates the performance of the IS. Finally, it is shown that with an appropriate choice of the estimation time, the severity in distortion can be effectively regulated.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Goldsmith, A., Jafar, S., Maric, I., Srinivasa, S.: Breaking Spectrum Gridlock With Cognitive Radios: An Information Theoretic Perspective. Proceedings of the IEEE 97(5), 894–914 (2009)CrossRefGoogle Scholar
  2. 2.
    Axell, E., Leus, G., Larsson, E., Poor, H.: Spectrum sensing for cognitive radio: State-of-the-art and recent advances. IEEE Signal Processing Magazine 29(3), 101–116 (2012)CrossRefGoogle Scholar
  3. 3.
    Sharma, S., Chatzinotas, S., Ottersten, B.: Exploiting polarization for spectrum sensing in cognitive satcoms. In: CROWNCOM, pp. 36–41, June 2012Google Scholar
  4. 4.
    Urkowitz, H.: Energy detection of unknown deterministic signals. Proceedings of the IEEE 55(4), 523–531 (1967)CrossRefGoogle Scholar
  5. 5.
    Kostylev, V.: Energy detection of a signal with random amplitude. In: ICC, vol. 3, pp. 1606–1610 (2002)Google Scholar
  6. 6.
    Digham, F., Alouini, M.-S., Simon, M.K.: On the energy detection of unknown signals over fading channels. In: ICC, vol. 5, pp. 3575–3579, May 2003Google Scholar
  7. 7.
    Herath, S., Rajatheva, N., Tellambura, C.: Unified approach for energy detection of unknown deterministic signal in cognitive radio over fading channels. In: ICC Workshops, pp. 1–5, June 2009Google Scholar
  8. 8.
    Mariani, A., Giorgetti, A., Chiani, M.: Energy detector design for cognitive radio applications. In: 2010 International Waveform Diversity and Design Conference (WDD), pp. 000053–000057, August 2010Google Scholar
  9. 9.
    Tandra, R., Sahai, A.: SNR Walls for Signal Detection. IEEE Journal of Selected Topics in Signal Processing 2(1), 4–17 (2008)CrossRefGoogle Scholar
  10. 10.
    Liang, Y.-C., Zeng, Y., Peh, E., Hoang, A.T.: Sensing-Throughput Tradeoff for Cognitive Radio Networks. IEEE Transactions on Wireless Communications 7(4), 1326–1337 (2008)CrossRefGoogle Scholar
  11. 11.
    Cardenas-Juarez, M., Ghogho, M.: Spectrum Sensing and Throughput Trade-off in Cognitive Radio under Outage Constraints over Nakagami Fading. IEEE Communications Letters 15(10), 1110–1113 (2011)CrossRefGoogle Scholar
  12. 12.
    Sharkasi, Y., Ghogho, M., McLernon, D.: Sensing-throughput tradeoff for OFDM-based cognitive radio under outage constraints. In: ISWCS, pp. 66–70, August 2012Google Scholar
  13. 13.
    Kaushik, A., Sharma, S.K., Chatzinotas, S., Ottersten, B., Jondral, F.K.: Estimation-Throughput tradeoff for underlay cognitive radio systems. In: IEEE Int. Conf. on Communications (ICC) - Cognitive Radio and Networks Symposium, June 2015 (to appear)Google Scholar
  14. 14.
    Kaushik, A., Mueller, M., Jondral, F.K.: Cognitive Relay: Detecting Spectrum Holes in a Dynamic Scenario. In: ISWCS, pp. 1–2, April 2013Google Scholar
  15. 15.
    Kay, S.: Fundamentals of Statistical Signal Processing: Detection theory. Prentice Hall Signal Processing Series. Prentice-Hall PTR (1998)Google Scholar
  16. 16.
    Gradshteyn, I.S., Ryzhik, I.M.: Table of Integrals, Series, and Products, 6th edn. Academic Press, San Diego (2000)MATHGoogle Scholar

Copyright information

© Institute for Computer Science, Social Informatics and Telecommunications Engineering 2015

Authors and Affiliations

  • Ankit Kaushik
    • 1
  • Shree Krishna Sharma
    • 2
  • Symeon Chatzinotas
    • 2
  • Björn Ottersten
    • 2
  • Friedrich Jondral
    • 1
  1. 1.Communications Engineering LabKarlsruhe Institute of Technology (KIT)KarlsruheGermany
  2. 2.SnT - Securityandtrust.lu, University of LuxembourgWalferdangeLuxembourg

Personalised recommendations