Enhanced Particle Swarm Optimization assisted Cooperative Spectrum Sensing in Cognitive Radio under Rayleigh Fading Scenario

Abstract

When performing cooperative spectrum sensing by using Soft Decision Fusion (SDF), the weighting coefficients play a major role in the detection performance. In this work, by utilizing the Enhanced Particle Swarm Optimization (EPSO) is optimization of the weighting coefficient vector is carried out. The EPSO selects the best weighting coefficients from the weighting coefficient vector. The detection accuracy of the EPSO technique is evaluated and contrasted with traditional PSO, GA (Genetic Algorithm) and also with traditional Soft-Decision Fusion (SDF) methods by using MATLAB simulations. From simulation results, it is inferred that the proposed technique outperforms all other Soft-Decision methods over Rayleigh channel. An increased detection performance is obtained as inferred from the results.