Cognitive radio technology is introduced to improve the spectrum utilization by allowing unlicensed users to share spectrum with licensed users in an opportunistic manner. Cognitive radio is still in the infancy stage. The conventional approaches based on analytical techniques for understanding and predicting the behavior of cognitive radio system can prove to be very difficult and inflexible in order to cope with the intricacy and complexity of the issues and challenges associated with its implementation. While dealing with cognitive radio, we have to deal with high degree of uncertainty and to tolerate capacity imprecision. Conventional approaches which are based on numerical analysis or crisp logic have characteristics of precision, are termed as hard computing approaches. Whereas, soft computing approaches like fuzzy logic, neural networks, genetic algorithm, probabilistic reasoning etc. have characteristic of approximation. The advantages of using soft computing techniques are capable to manage tolerance for imprecision and uncertainty, lower cost of computation and high Machine Intelligence Quotient (MIQ).
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Cognitive radio technology is introduced to improve the spectrum utilization by allowing unlicensed users to share spectrum with licensed users in an opportunistic manner. Cognitive radio is still in the infancy stage. The conventional approaches based on analytical techniques for understanding and predicting the behavior of cognitive radio system can prove to be very difficult and inflexible in order to cope with the intricacy and complexity of the issues and challenges associated with its implementation. While dealing with cognitive radio, we have to deal with high degree of uncertainty and to tolerate capacity imprecision. Conventional approaches which are based on numerical analysis or crisp logic have characteristics of precision, are termed as hard computing approaches. Whereas, soft computing approaches like fuzzy logic, neural networks, genetic algorithm, probabilistic reasoning etc. have characteristic of approximation. The advantages of using soft computing techniques are capable to manage tolerance for imprecision and uncertainty, lower cost of computation and high Machine Intelligence Quotient (MIQ).
Maninder Jeet Kaur did her PhD from Dr B R Ambedkar National Institute of Technology, Jalandhar, India. She has completed her B.Tech in Electronics and Communication Engineering in 2005. She completed her M.Tech in 2007. She was selected for Commonwealth Split Site Doctoral Fellowship-2010 at United Kingdom.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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