Enhanced Particle Swarm Optimization assisted Cooperative Spectrum Sensing in Cognitive Radio under Rayleigh Fading Scenario
1*R.Harikrishnan, Ph.D. Department, Electronics and Communication Engineering. Annamalai University, Chidambaram.
2Dr.V.Padmathilagam, Associate Professor, Electrical Engineering in Annamalai University, Chidambaram.
Manuscript received on November 23, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 3859-3863 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B4426129219/2019©BEIESP | DOI: 10.35940/ijeat.B4426.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
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.
Keywords: Cooperative spectrum sensing, Rayleigh fading channel, Soft decision fusion, Particle Swarm Optimization, Enhanced particle swarm optimization, Weighting coefficient vector.