Spectrum Sensing of Interleaved SC-FDMA Signals in Cognitive Radio Networks

This paper develops a spectrum sensing technique for interleaved single-carrier frequency-division multiple access (SC-FDMA) systems. By designing a metric that exploits cyclostationary features of interleaved SC-FDMA signals, the authors establish a framework for signal detection. Using Gaussian approximation for this metric, the parameters of the metric distributions under two hypotheses are derived, and both hypotheses are examined by the Neyman–Pearson test. They validate the accuracy of the Gaussian approximation by comparing theoretical and simulated metric histograms. The performance of the proposed method is presented for additive white Gaussian noise and multipath Rayleigh fading channels. They also investigate the effect of the block length, the number of users, the metric window length, and the presence of the pilot signals on the detection performance. Through comparative performance evaluation, the authors demonstrate the superiority of their proposed detection scheme over energy detection and the detection method based on autocorrelation of the cyclic prefix (CP). They obtain similar detection performance to that of the mentioned methods at about 8–13 dB lower signal-to-noise ratio (SNR). It is noteworthy that the complexity of the method is comparable to that of the energy detection and slightly higher than that of CP detection.

• Record URL:
  • https://doi.org/10.1109/TVT.2014.2331695
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00189545
• Supplemental Notes:
  • Abstract reprinted with permission of IEEE.
• Authors:
  • Mirdamadi, A
  • Sabbaghian, M
• Publication Date: 2015-4

Language

• English

Media Info

• Media Type: Web
• Pagination: pp 1633-1637
• Serial:
  • IEEE Transactions on Vehicular Technology
  • Volume: 64
  • Issue Number: 4
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 0018-9545
  • Serial URL: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=25

Subject/Index Terms

• TRT Terms: Accuracy; Frequency division multiple access; Histograms; Multipath transmission; Networks; Sensors; Spectrum analysis
• Subject Areas: Data and Information Technology; Highways; Vehicles and Equipment; I90: Vehicles;

Filing Info

• Accession Number: 01564630
• Record Type: Publication
• Files: TRIS
• Created Date: May 26 2015 4:12PM