A Cooperative Sensor Set Selecting Algorithm under Spatial Correlation

The problem of sensor set selection for cooperative spectrum sensing in cognitive radio networks is considered in this paper. To the best of our knowledge, this is the first effort to select sensor set for cooperative spectrum sensing in cognitive radio. Under spatial correlation channels, the cooperative gain of the newly added cooperative sensor decreases and converges to zero as the number of cooperative sensors increases. Meanwhile, the system resources usage efficiency decreases as the number of cooperative sensors increases, since the consumption of system resources, such as the total transmission power of the signal measurements and the amount of overhead traffic in the cognitive radio network, grows approximately linearly with the number of cooperative sensors. Therefore, the number of cooperative sensors to use is a compromise between sensing performance and system resources usage efficiency. A greedy based cooperative sensor set selecting algorithm is proposed which can use a threshold acquired by compromising between sensing performance and resources usage efficiency to select a cooperative sensor set. Numerical results illustrate the effectiveness and reliability of the proposed sensor set selecting algorithm.