A cultural bacterial foraging algorithm for spectrum sensing of cognitive radio

In order to solve spectrum sensing problem, this paper proposes a cultural bacterial foraging algorithm (CBFA) based on bacterial foraging optimization algorithm (BFOA) and knowledge strategy of cultural algorithm. The proposed CBFA applies the knowledge strategy and new movement equations to bacterial foraging optimization, and thus has the advantages of low computational complexity and fast convergence. As a key step of CBFA, chemotactic movement is modelled as guiding cultural behaviour and thus may improve the capability of BFOA to find the optimum solution. Then we applied the proposed CBFA in cooperative spectrum sensing of cognitive radio (CR). We compare the performance of the proposed CBFA with classical BFOA, shuffled frog leaping algorithm (SFLA) and particle swarm optimization (PSO). The simulation results show that CBFA has a better searching speed and an obvious improvement in accuracy.