Efficient detection of primary users in cognitive radio networks

Authors:
Xuetao Chen;Tamal Bose;S. M. Hasan;Jeffrey H. Reed
Affiliations:
Bradley Department of Electrical and Computer Engineering, Wireless@VT, 432 Durham Hall, Virginia Tech, Blacksburg, VA 24061, USA.;Bradley Department of Electrical and Computer Engineering, Wireless@VT, 432 Durham Hall, Virginia Tech, Blacksburg, VA 24061, USA.;Bradley Department of Electrical and Computer Engineering, Wireless@VT, 432 Durham Hall, Virginia Tech, Blacksburg, VA 24061, USA.;Bradley Department of Electrical and Computer Engineering, Wireless@VT, 432 Durham Hall, Virginia Tech, Blacksburg, VA 24061, USA
Venue:
International Journal of Communication Networks and Distributed Systems
Year:
2012

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Abstract

This paper proposes an approach to detect the primary user during the communication of the secondary users, using the concept of interference detection in the presence of a desired signal. The detection problem is first formulated as a multi-class classification problem. The pattern with medium bit error rate (BER) and low interference to signal power ratio (ISR) is identified as the most difficult case. A classifier based on a support vector machine (SVM) is proposed to solve this problem. Simulation results yield 76% classification accuracy with ISR larger than -10 dB and a heterogenous channel condition between the primary link and secondary link. Both the channel vacation time and the usage of idle time can be reduced by the proposed approach.