Adaptive transmission in cognitive radio networks

  • Authors:
  • Yuling Zhang;Fuzeng Zhang;Wenwei He

  • Affiliations:
  • School of Computer Science and Technology, Ludong University, Yantai, Shandong;School of Computer Science and Technology, Ludong University, Yantai, Shandong;School of Computer Science and Technology, Ludong University, Yantai, Shandong

  • Venue:
  • CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
  • Year:
  • 2009

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Abstract

In this paper, we investigate the adaptive transmission in cognitive radio networks using genetic algorithms (GA), the relevant communication parameters are optimized in a dynamic wireless channel environment. Firstly, we give the variables representing the transmission parameters that can be controlled by the system, several objective functions in different layers must also be determined to define how the cognitive radio should operate, then we invoke genetic algorithms for iteratively finding the optimum parameters toward different quality of service (QoS) based on the channel environment. The channel state information is assumed to be perfectly known by the transmission side. Simulation results show that our implementation outperforms the conventional scheme for with parameters are optimized at each layer separately.