Cooperative Spectrum Sensing with Distributed Detection Threshold

This paper proposes a cooperative spectrum sensing algorithm based on distributed fusion strategy and maintained probability of false alarm for cognitive radio. It further introduces a reporting strategy that discusses how cooperative sensing in distributed manner can select among possible candidate nodes in order to reduce bandwidth requirement. We adopted a dynamic distributed architecture for cooperative sensing based on the link quality of the candidate nodes and found condition on the channel quality for cooperation to be beneficial. Using probability of detection, and Bit Error Rate (BER) as performance metrics we evaluated the performance improvement of distributed cooperation over direct cooperation and non-cooperative sensing. We used analytical formulation with possible candidate selection criteria to investigate and maximize the distributed cooperation gain. By employing such distribution and selection technique, the reporting error due to the fading channel is reduced based on number of candidate nodes. Results show that the method effectively improve performance of sensing, it increase the probability of detection up to 0.9 at <;0.1 probability of false alarm. Sensitivity requirement is reduced with network scale and the node number to participate in decision fusion is reduced about 42% at probability of false alarm 0.1. Receiver operation characteristic (ROC) curve has obvious improvement compared with existing methods.