An ant colony optimization algorithm for spectrum assignment in cognitive radio networks

To solve the spectrum assignment issue in cognitive network, a new ant optimization algorithm for spectrum assignment is proposed in this paper. In the cognitive radio network model, where primary and secondary users are coexistent, ants visit secondary users as the node, and leave pheromones using channel rewards. By this way the optimized parallel algorithm is implemented. Compared with the traditional spectrum assignment method, it can implement enhanced accumulation by learning, fast coverage to the optimal resolution, and improve the performance in the whole network average throughput. The method is analyzed. Simulation results verify the stability and validity of the method.