4.4 Article

I3S: Intelligent spectrum sensing scheme for cognitive radio networks

出版社

SPRINGEROPEN
DOI: 10.1186/1687-1499-2013-26

关键词

Cognitive radio networks; Spectrum sensing; Energy detection; Cyclostationary detection; Matched filter

资金

  1. CITRC (Convergence Information Technology Research Center) support program [NIPA-2012-H0401-12-1003]
  2. MKE
  3. Seoul RBD Program [SS110012C0214831]
  4. Special Disaster Emergency R&D Program from National Emergency Management Agency through Kyungil University [2012-NEMA10-002-01010001-2012]
  5. National Emergency Management Agency (NEMA), Republic of Korea [2012-NEMA10-002-01010000-2012] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

向作者/读者索取更多资源

Reliable spectrum sensing is one of the most crucial aspects for the successful deployment of cognitive radio (CR) technology. For CR, it is not possible to transmit on a licensed band and sense it simultaneously, therefore sensing must be interleaved with transmission. Spectrum sensing in CR is challenged by a number of uncertainties, which degrade the sensing performance and in turn require much more time to achieve the targeted sensing efficiency. Hence, the authors propose a spectrum sensing scheme which obtains reliable results with less mean detection time. First, the scheme determines a better matched filter, or a combination of energy and cyclostationary detectors based on the power and band of interest. In the combined energy and cyclostationary detector, an energy detector with a bi-threshold is used, and the cyclostationary detector is applied only if the energy of the signal lies between two thresholds. Second, sensing is performed by the selection choice resulting from the first step. To evaluate the scheme's performance, the results are compared with those where only an energy detector, matched filter, or cyclostationary detector are performed. The performance metrics are the probability of detection, probability of false alarm, and mean detection time.

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