关键词： 认知无线电, 协作式频谱感知, 粒子群优化, 能量检测, 修正系数

Abstract:

To improve the computation efficiency and the sensing performance,a new linear cooperative spectrum sensing algorithm is developed for cognitive radio.In the proposed method,the improved particle swarm optimization (PSO) is utilized to obtain the optimal weight vector to maximize the probability of detection by dynamically changing the inertia weight in each iteration.Due to using the of time varying inertia weight,the proposed PSO based cooperative spectrum sensing algorithm has good global exploration capability at the beginning of the swarm flight,and with the increase in the number of iterations,especially in the late swarm flight,has good local search capability.The simulation results illustrate that the proposed method has faster convergence speed than the method based on the traditional PSO.At the same time,it shows better detection performance than both the method based on modified deflection coefficient  and the method based  on traditional PSO.The simulation results under different sensing scenarios validate the effectiveness of the proposed cooperative sensing algorithm.

Key words: cognitive radio, cooperative spectrum sensing, particle swarm optimization, energy detection, modified deflection coefficient