Cooperation Spectrum Sensing for Cognitive Radio Networks Based on the Bacteria Foraging Optimization Algorithm

Wang Yonghua; Li Yuehong; Yang Jian; Wan Pin; Deng Qin
March 2012
International Journal of Digital Content Technology & its Applic;Mar2012, Vol. 6 Issue 4, p24
Academic Journal
Spectrum sensing is one of the most challenging issues in cognitive radio networks. The individual cognitive radio user may not be able to reliably detect the existence of a primary radio user due to the channel fading and its geographic separation. In order to enhance the reliability of the spectrum sensing, the cooperative spectrum sensing can be used. In this paper, a cooperative spectrum sensing method based on the Bacteria Foraging Optimization Algorithm (BFOA) is proposed. In this method, spectrum sensing is based on the linear cooperation framework, and the weight vectors are optimized by the BFOA since the BFOA has strong global search capability. The performance of the proposed cooperation schemes is evaluated and compared with the Shuffled Frog Leaping Algorithm (SFLA)-based and Modified Deflection Coefficient (MDC)-based algorithms. Simulation results show that the proposed cooperative spectrum sensing method based on BFOA gives the higher detection probability than the MDC-based method and SFLA-based method under the condition of false alarm probability is relatively low. And in different noise environments, the probability of miss-detection of BFOA is higher than that of SFLA and MDC. These show the superiority and robustness of the proposed cooperative spectrum sensing method based on BFOA.


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