KSII Transactions on Internet and Information Systems (TIIS)

  • 제3권5호
  • /
  • Pages.461-474
  • /
  • 2009
  • /
  • 1976-7277(pISSN)
  • /
  • 1976-7277(eISSN)
한국인터넷정보학회 (Korean Society for Internet Information)
권호 표지
DOI QR코드

DOI QR Code

A Novel Cluster-Based Cooperative Spectrum Sensing with Double Adaptive Energy Thresholds and Multi-Bit Local Decision in Cognitive Radio

  • Van, Hiep-Vu (The School of Electrical Engineering, University of Ulsan) ;
  • Koo, In-Soo (The School of Electrical Engineering, University of Ulsan)
  • 발행 : 2009.10.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

The cognitive radio (CR) technique is a useful tool for improving spectrum utilization by detecting and using the vacant spectrum bands in which cooperative spectrum sensing is a key element, while avoiding interfering with the primary user. In this paper, we propose a novel cluster-based cooperative spectrum sensing scheme in cognitive radio with two solutions for the purpose of improving in sensing performance. First, for the cluster header, we use the double adaptive energy thresholds and a multi-bit quantization with different quantization interval for improving the cluster performance. Second, in the common receiver, the weighed HALF-voting rule will be applied to achieve a better combination of all cluster decisions into a global decision.

키워드

참고문헌

  1. Federal Communications Commission, Spectrum Policy Task Force, Rep. ET Docket no. 02-135, Nov. 2002.
  2. Y. Hur, J. Park, W. Woo, K. Lim, C.-H. Lee, H. S. Kim, and J. Laskar, “A wideband analog multi-resolution spectrum sensing (MRSS) technique for cognitive radio (CR) systems,” Proc. IEEE Int. Symp. Circuit and System, Greece, pp. 4090-4093, May 2006.
  3. A. Sahai, N. Hoven, and R. Tandra, “Some fundamental limits on cognitive radio,” Proc. Allerton Conf. on Communications, control, and computing, Monticello, Oct. 2004.
  4. G. Ganesan and Y. G. Li, “Cooperative spectrum sensing in cognitive radio networks,” Proc. IEEE Symp. New Frontiers in Dynamic Spectrum Access Networks (DySPAN05), Baltimore, USA, pp. 137-143, Nov. 2005.
  5. A. Ghasemi and E. S. Sousa, “Collaborative spectrum sensing for opportunistic access in fading environments,” Proc. IEEE Symp. New Frontiers in Dynamic Spectrum Access Networks (DySPAN05), Baltimore, USA, pp. 131-136, Nov. 2005.
  6. S. M. Mishra, A. Sahai, and R. Brodersen, “Cooperative sensing among cognitive radios,” Proc. IEEE Int. Conf. Commun., Turkey, vol. 4, pp. 1658-1663, June 2006.
  7. D. Cabric, S. M. Mishra, and R. W. Brodersen, “Implementation issues in spectrum sensing for cognitive radios,” Proc. of Asilomar Conf. on Signals, Systems and Computers, Pacic Grove, CA, USA, pp. 772-776, Nov. 2004.
  8. C. Sun, W. Zhang, and K. B. Letaief, “Cluster-based cooperative spectrum sensing for cognitive radio systems,” Proc. IEEE Int. Conf. Commun., Glasgow, Scotland, UK, pp. 2511-2515, June 2007.
  9. Z. Chair, P. K. Varshney, “Optimal data fusion in multiple sensor detection systems,” IEEE Trans. Aerospace Electron. Syst., pp. 98-101, Jan. 1986. https://doi.org/10.1109/TAES.1986.310699
  10. V. I. Kostylev, “Energy detection of a signal with random amplitude,” Proc. IEEE Int. Conf. Commun., New York, pp. 1606-1610, Apr.-May 2002.
  11. F. F. Digham, M.-S. Alouini, and M. K. Simon, “On the energy detection of unknown signals over fading channels,” Proc. IEEE Int. Conf. Commun., Anchorage, AK, USA, pp. 3575-3579, May 2003.
  12. Jiang Zhu, Zhengguang Xu, Furong Wang, Benxiong Huang, Bo Zhang, “Double Threshold Energy Detection of Cooperative Spectrum Sensing in Cognitive Radio,” 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications 2008 (CrownCom 2008), vol., no., pp. 1-5, May 2008.
  13. Lei Chen; Jun Wang; Shaoqian Li, “Cooperative Spectrum Sensing with multi-bit Local Sensing Decisions in Cognitive Radio Context,” Wireless Communications and Networking Conference, 2008 (WCNC 2008) pp. 570-575, Mar.-Apr. 2008,.

피인용 문헌

  1. A Quantization-Based Multibit Data Fusion Scheme for Cooperative Spectrum Sensing in Cognitive Radio Networks vol.18, pp.2, 2009, https://doi.org/10.3390/s18020473