A two-threshold cooperative spectrum sensing algorithm using swarm intelligence

In recent years, we have witnessed a rapid growth in wireless communications, especially in providing quality multimedia services. As a result, there is ever growing demand for radio spectrum. The present static frequency allocation cannot accommodate this demand as most of the spectrum is occupied by licensed users and is used inefficiently. Cognitive Radio (CR) has emerged as an effective technology to solve the inefficiency of spectrum usage by opportunistically accessing the under-utilized frequency bands. In this paper, we propose a Hybrid PSO-OR (Particle Swarm Optimization and OR) algorithm which uses a double threshold energy detector to perform spectrum sensing. The fusion centre, in the cognitive radio network, collects local decisions as well as energy values from secondary users. Particle Swarm Optimization (PSO) is then used to optimize the decision from the “fuzzy” secondary users. A final collective decision is made based on local decisions and observation values. This way, double thresholds will help in reducing the communication overhead over the reporting channel compared to single threshold data fusion techniques with a negligible loss in performance. Our results show that the proposed Hybrid PSO-OR algorithm outperforms the Hybrid EGC-OR algorithm.