Optimized Reliable Data Combining Cooperative Spectrum Sensing Method in Cognitive Radio Networks

Spectrum sensing is one of the most important tasks of each cognitive radio network. Cooperation among secondary users, by increasing the sensing accuracy can improve the network throughput, but also increases the energy consumption of cognitive radio network. In this paper, we propose the reliable data combining method for cooperative spectrum sensing, according to which the fusion center by using two threshold values, makes the final decision only if it is confident enough in validity of received local data. Otherwise, an additional sensing will be performed. Throughput maximization problems under interference constraints are formulated for both soft and hard fusion schemes and the optimal sensing time and threshold values are obtained. Simulations show that for all SNRs, higher absolute throughput and also higher throughput per energy consumption are accessible, rather than conventional cooperative sensing. Moreover, for a large range of SNRs the less energy is consumed.