Cooperative spectrum sensing based on an efficient adaptive artificial bee colony algorithm

In this paper, we present an efficient adaptive artificial bee colony (EA-ABC) algorithm that includes an adaptive mutation mechanism, guaranteed convergence mechanism and optimal tracking mechanism. The EA-ABC algorithm is applied to cooperative spectrum sensing for a cognitive radio field. An efficient sensing scheme can reduce the false alarm probability and enhance the detection probability, which can improve spectrum utilization. Simulations are conducted to compare the performance of the proposed cooperative spectrum sensing method based on the EA-ABC algorithm with that of the cooperative spectrum sensing method using the ABC, particle swarm optimization (PSO), and modified PSO algorithms. The simulation results validate the effectiveness and reliability of the proposed method and demonstrate that EA-ABC-based can achieve higher detection probability than other methods under the same false alarm probability.