An optimal data fusion rule in cluster-based cooperative spectrum sensing

  • Authors:

  • Hiep-Vu Van;Insoo Koo

  • Affiliations:

  • School of Electrical Engineering, University of Ulsan, Ulsan, Republic of Korea;School of Electrical Engineering, University of Ulsan, Ulsan, Republic of Korea

  • Venue:
  • ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper, we consider a cluster-based cooperative spectrum sensing approach to improve the sensing performance of cognitive radio (CR) network. In the cluster-based cooperative spectrum sensing, CR users with the similar location are grouped into a cluster. In each cluster, the most favorable user namely cluster header, will be chosen to collect data from all CR users and send the cluster decision to common receiver who makes a final decision on the presence of primary user. In the cluster-based cooperative spectrum sensing, data fusion rule in the cluster takes an important role to reduce the rate of reporting error. Subsequently we propose optimal fusion rule for each cluster header with which we can minimize the sum of probability of false alarm and probability of missed detection in each cluster header.