Abstract
Weighting the coefficients vector is the principal factor influencing the detection performance of cognitive radio networks that uses soft-detection fusion (SDF) based cooperative spectrum sensing. Maximal ratio combining- (MRC-), equal gain combining- (EGC-) and continuous genetic algorithm- (CGA-) based SDF are well suited for optimizing the detection performance and thus ensure safe access of spectrum by CR users. However the mentioned methods suffer from slow convergence and/or sub-optimality. In this paper, the use of particle swarm optimization (PSO) algorithm under MINI-MAX criterion is proposed to optimize the weighting coefficients vector so that the total probability of decision error is minimized. The performance of the PSO-based proposed method is examined and compared with GA-based technique as well as other conventional SDF schemes through computer simulations. Numerical results confirm the effectiveness of the proposed method.
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