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Chaotic Prediction Based Channel Sensing in CR System

CR 시스템에서 Chaotic 예측기반 채널 센싱기법

  • Gao, Xiang (Dept. of Electrical Electronic & communication Engineering, KoreaTech) ;
  • Lee, Juhyeon (Dept. of Electrical Electronic & communication Engineering, KoreaTech) ;
  • Park, Hyung-Kun (Dept. of Electrical Electronic & communication Engineering, KoreaTech)
  • Received : 2012.10.23
  • Accepted : 2012.11.28
  • Published : 2013.01.01

Abstract

Cognitive radio (CR) has been recently proposed to dynamically access unused-spectrum. Since the spectrum availability for opportunistic access is determined by spectrum sensing, sensing control is identified as one of the most crucial issues of cognitive radio networks. Out-of-band sensing to find an available channels to sense. Sensing is also required in case of spectrum hand-off. Sensing process needs to be done very fast in order to enhance the quality of service (QoS) of the CR nodes, and transmission not to be cut for longer time. During the sensing, the PU(primary user) detection probability condition should be satisfied. We adopt a channel prediction method to find target channels. Proposed prediction method combines chaotic global method and chaotic local method for channel idle probability prediction. Global method focus on channel history information length and order number of prediction model. Local method focus on local prediction trend. Through making simulation, Proposed method can find an available channel with very high probability, total sensing time is minimized, detection probability of PU's are satisfied.

Keywords

References

  1. FCC, Spectrum Policy Task Force Report, ET Docket no.02-155, Nov, 2002.
  2. J. Mitola, G.Q. Maguire, "Cognitive radio: making software radios more personal", IEEE Personal Communications, vol. 6, no. 4, pp. 13-18, Aug. 1999. https://doi.org/10.1109/98.788210
  3. Ling Luo, and Sumit Roy, "Analysis of search schemes in cognitive radio", in 2nd IEEE Workshop on Networking Technologies for Software Define Radio Networks, pp. 17-24, 2007
  4. Ramzi Saifan, Ahmed E.Kamal, Yong Guan, "Efficient spectrum searching and monitoring in cognitive radio network", IEEE International Conference on MAHSS, pp.520-529, 2011
  5. Jinhu Lv, Junan Lu, Shihua Chen, "Chaotic time series analysis and application", Wuhan University press, 2002