Optimization of hard fusion based spectrum sensing for energy-constrained cognitive radio networks

The detection reliability of a cognitive radio network improves by employing a cooperative spectrum sensing scheme. However, increasing the number of cognitive radios entails a growth in the cooperation overhead of the system. Such an overhead leads to a throughput degradation of the cognitive radio network. Since current cognitive radio networks consist of low-power radios, the energy consumption is another critical issue. In this paper, throughput optimization of the hard fusion based sensing using the k-out-of-N rule is considered. We maximize the throughput of the cognitive radio network subject to a constraint on the probability of detection and energy consumption per cognitive radio in order to derive the optimal number of users, the optimal k and the best probability of false alarm. The simulation results based on the IEEE 802.15.4/ZigBee standard, show that the majority rule is either optimal or almost optimal in terms of the network throughput.