Novel Incremental Spectrum Sensing in Cooperative Cognitive Radio Networks

In this paper, we consider a novel spectrum sensing system in which firstly, the fusion center (FC) senses and makes the own decision then if its sensing result is not useful for achieving the final decision, the local observations from the cognitive users (CUs) will be required. Moreover, in case that FC needs the results from CUs, we will choose only CU having the highest collected energy to send its local decision to FC. Based on this selecting method, the number of sensing bits can be reduced; hence, we can save the power and the bandwidth for reporting stage in the cognitive radio network (CRN). The mathematical analysis of the key metrics of the sensing schemes (probability of detection, false alarm, e.g.) will be investigated and confirmed by the Monte-Carlo simulation results to show the performance enhancement of the proposed schemes.