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Cognitive Radio and Its Impact of Throughput with Channel Optimization Techniques

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Spectrum scarcity has gained a great challenge in the current scenarios of wireless communication. In order to optimize the spectrum usage on the other hand cognitive networks has shown a considerable growth. This paper tries to focus on optimization with particle swarm optimization in cognitive networks (PSO-CN) and tree seed algorithm in cognitive networks (TSA-CN) which are multichannel based. The algorithm is based on higher probability of detection and throughput with lower probability of false alarm. The lower probability of false alarm has been achieved without compromising on the transmission rate with TSA-CN. The convergence time is found to be quicker with TSA-CN. Results with matlab based simulator shows there is an increase in throughput and decrease in false alarm with TSA algorithm than the PSO algorithm.
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Keywords: Multichannel; PSO-CN; TSA-CN

Document Type: Research Article

Affiliations: 1: Department of Electronics and Communication Engineering, Government Polytechnic College, Perambalur 621104, India 2: Department of Electronics and Communication Engineering, Easwari Engineering College, Chennai 600089, India

Publication date: 01 January 2017

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  • Journal of Computational and Theoretical Nanoscience is an international peer-reviewed journal with a wide-ranging coverage, consolidates research activities in all aspects of computational and theoretical nanoscience into a single reference source. This journal offers scientists and engineers peer-reviewed research papers in all aspects of computational and theoretical nanoscience and nanotechnology in chemistry, physics, materials science, engineering and biology to publish original full papers and timely state-of-the-art reviews and short communications encompassing the fundamental and applied research.
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