Cognitive Radio parameters optimization using Bio-Inspired Algorithms

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Details

Cognitive Radio Engine model optimizes wireless transmission parameters for spectrum management and decision supports, results analyzed and compared among multi-channel with algorithms based on Base-10 Genetic Algorithms (GA), Particle Swarm Optimization (PSO)and hybrid of GA+PSO. Multi-objective fitness functions established the relationships among the environmental parameters, transmission parameters, and objectives of QoS performance. Using theoretically relationships between various different parameters and the weighted cumulative sum approach, equations for each objective to be used within Cognitive Radio engines were developed. The objectives of these multi-objective fitness functions were controlled by the values of the weights on each defined function. A robust technique for spectrum mobility of secondary users based on DNA inspired computing, satisfies the solution to problem given by S. Haykin paper "Cognitive Radio: Brain-Empowered Wireless Communications". However, this involve only one transmission parameter (i.e. received power) and at last, cognitive radio security threats discussed based on Simulink model.

Autorentext

Dr. Santosh Kumar Singh (M.Sc. PhD) is presently working as Assistant Professor, Department of Biotechnology, S.B.S.P.G.I Biomed Sci & Res, Dehradun, Uttarakhand, India. He was awarded his Ph.D. (Biotechnology) from University of Allahabad. He is working in the area of biodiversity conservation. He has published more than 50 research papers.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783848441426
    • Sprache Englisch
    • Auflage Aufl.
    • Größe H220mm x B220mm
    • Jahr 2012
    • EAN 9783848441426
    • Format Kartonierter Einband (Kt)
    • ISBN 978-3-8484-4142-6
    • Titel Cognitive Radio parameters optimization using Bio-Inspired Algorithms
    • Autor Santosh Kumar Singh
    • Untertitel Cognitive Radio parameters optimization based on GA, PSO and Spectrum mobility based on DNA inspired computing
    • Herausgeber LAP Lambert Academic Publishing
    • Anzahl Seiten 160
    • Genre Informatik

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