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Multiobjective Multivariate Optimization of Joint Spectrum Sensing and Power Control in Cognitive Wireless Networks

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  • Hieu Van Dang

    (University of Manitoba, Winnipeg, Canada)

  • Witold Kinsner

    (Cognitive Systems Laboratory, Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, Canada & Telecommunications Research Laboratories (TRLabs), Winnipeg, Canada)

Abstract

In this paper, the authors investigate trade-off factors in designing efficient spectrum sensing and optimal power control techniques for a multichannel, multiple-user cognitive wireless network. They introduce the problem of joint spectrum sensing and power control as a maximization of the network throughput and a minimization of the interference to the network. These two optimization objectives can be achieved by a joint determination of sensing and transmission parameters of the secondary users, such as sensing times, decision threshold vectors, and power allocation vectors. There is a conflict between these two objectives, thus a multiobjective optimization problem is introduced. The authors propose an analytical approach based on Newton's methods and nonlinear barrier method to solve this large-scale joint multiobjective optimization problem.

Suggested Citation

  • Hieu Van Dang & Witold Kinsner, 2016. "Multiobjective Multivariate Optimization of Joint Spectrum Sensing and Power Control in Cognitive Wireless Networks," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 10(2), pages 26-51, April.
  • Handle: RePEc:igg:jcini0:v:10:y:2016:i:2:p:26-51
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