PEI Qingqi, LI Hongning, LIU Xianjun. Neighbor Detection-Based Spectrum Sensing Algorithm in Distributed Cognitive Radio Networks[J]. Chinese Journal of Electronics, 2017, 26(2): 399-406. doi: 10.1049/cje.2016.06.018
Citation: PEI Qingqi, LI Hongning, LIU Xianjun. Neighbor Detection-Based Spectrum Sensing Algorithm in Distributed Cognitive Radio Networks[J]. Chinese Journal of Electronics, 2017, 26(2): 399-406. doi: 10.1049/cje.2016.06.018

Neighbor Detection-Based Spectrum Sensing Algorithm in Distributed Cognitive Radio Networks

doi: 10.1049/cje.2016.06.018
Funds:  This work is supported by the National Natural Science Foundation of China (No.U1401251, No.U1536202, No.613731707), China Postdoctoral Science Foundation (No.2015M572528), Fundamental Research Funds for the central Universities (No.JB150114), and China Scholarship Council (CSC).
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  • Corresponding author: LI Hongning (corresponding author) received the B.S. degree in School of Science and M.S. degree in School of Telecommunications Engineering from Xidian University on 2007 and 2010, respectively, and the Ph.D. degree in School of Computer Science and Technology from Xidian University, Xi'an, China, in 2014. Her research interests include wireless networks and security, security and privacy in cognitive radio networks. (
  • Received Date: 2015-03-31
  • Rev Recd Date: 2015-06-25
  • Publish Date: 2017-03-10
  • Security issues of spectrum sensing have drawn a lot of attentions in Cognitive radio networks (CRNs). Malicious users can mislead the network to make wrong decision about the states of channels by tampering spectrum sensing data. To defense against Spectrum sensing data falsification (SSDF) attack, we propose a neighbor detection-based spectrum sensing algorithm in distributed CRNs, which can detect attackers with the help of neighbors during spectrum sensing to improve the accuracy of decision making. The proposed scheme can also guarantee the connectivity of the network. Simulation results illustrate that the proposed scheme can defense against SSDF attacks effectively and reach the unified information of spectrum sensing data.
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