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Subrat SaurabhAuthor of Kuch Woh PalDr Aniket Kumar is currently working as an Associate Professor & Head in the School of Electronics, Electrical & Mechanical Engineering, SIET, Meerut. He joined the institute in the year 2015. He is actively involved in various academic and administrative responsibilities at the University level and School levels. Presently, he is guiding 02 students at the Doctorate level. He has also received a TEACHER INNOVATION AWARD from Sri Aurobindo Society, for SUSTAINABLE EFFORTS TOWARDS PROMOTING JOYFUL AND EXPERIENTIAL TEACHING. His research interest includes Digital Systems Design, Signal ProcessRead More...
Dr Aniket Kumar is currently working as an Associate Professor & Head in the School of Electronics, Electrical & Mechanical Engineering, SIET, Meerut. He joined the institute in the year 2015. He is actively involved in various academic and administrative responsibilities at the University level and School levels. Presently, he is guiding 02 students at the Doctorate level. He has also received a TEACHER INNOVATION AWARD from Sri Aurobindo Society, for SUSTAINABLE EFFORTS TOWARDS PROMOTING JOYFUL AND EXPERIENTIAL TEACHING. His research interest includes Digital Systems Design, Signal Processing, and Vedic Mathematics.
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Spectrum sensing mechanisms enable Cognitive Radio networks to detect Primary users (PUs) and utilize spectrum holes for Secondary user (SU) transmission. In this paper, highly efficient cost optimization of Particle Swarm Optimization is proposed i.e. PSO-ACO. Hybridization of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) significantly increases the detection rate as Ant Colony Optimization (ACO) accelerates from false minima which reduc
Spectrum sensing mechanisms enable Cognitive Radio networks to detect Primary users (PUs) and utilize spectrum holes for Secondary user (SU) transmission. In this paper, highly efficient cost optimization of Particle Swarm Optimization is proposed i.e. PSO-ACO. Hybridization of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) significantly increases the detection rate as Ant Colony Optimization (ACO) accelerates from false minima which reduces the false minima. With this, throughput increases upto 92% and error rate reduces upto 10-3. PSO-ACO hybridization significantly out performs and fastly converge because of ACO optimization
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