Robust collaborative spectrum sensing based on beta reputation system
Collaborative spectrum sensing has been widely accepted as a promising approach to improve spectrum sensing performance by exploiting spatial diversity of cognitive radio users. However, in the presence of malfunctioning or misbehaved users, performance of collaborative spectrum sensing deteriorates significantly. In this paper, a credibility based mechanism for collaborative spectrum sensing using beta reputation system has been introduced. Our proposed method works well even if the total number of misbehaved users is unknown. In the proposed scheme, fusion center assigns weight to each user observation based on individual user credibility score. User credibility score is calculated using beta reputation system and simulation results show that proposed scheme significantly improves the reliability of aggregated data in the presence of falsified users.