New optimization method for cooperative spectrum sensing in cognitive radio networks

This paper proposes new method to optimize the overall performance in hard cooperative spectrum sensing in cognitive radio (CR) networks. Two optimization strategies are proposed in order to optimize the overall performance by controlling the number of locally sensed samples at each CR. The proposed strategies contribute to the methods in the literature by taking their performances to the optimist point. Additionally, the effects of spectrum sensing technique type that used locally at each CR, the number of locally sensed samples, the local SNR, and the total number of cooperated CRs on the optimal fusion rule are investigated. An energy detector (ED) and multitaper (MTM) spectrum sensing techniques are examined as local spectrum sensing techniques. The optimal number of sensed samples that minimizes the total error to zero, is found as 417 and 10060 samples when MTM and ED are used, respectively, with local SNR= 10dB and 10 CRs cooperate sensing. The optimal fusion rule is found as 5 out 10 in this case. Thus, using MTM in cooperative sensing is much faster than using ED.