Efficient detection of primary users in cognitive radio networks. (1st January 2012) - Chen, Xuetao; Bose, Tamal; Hasan, S.M.; Reed, Jeffrey H.
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.