A study of data fusion and decision algorithms based on cooperative spectrum sensing

Authors:
Qin Qin;Zeng Zhimin;Guo Caili
Affiliations:
College of Electrical Engineering & Information Science, China Three Gorges University, Yichang, China;School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China;School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China
Venue:
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
Year:
2009

Citing 2
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Decision Fusion of Cooperative Spectrum Sensing for Cognitive Radio under Bandwidth Constraints

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Abstract

The cooperative operation can improve the sensing performance of cognitive radio networks and reduce the sensing time. Combining multiple cognitive users' local detection results and making accurate judgment is essential to improve cooperative gain. According to uploaded information from cognitive users, hard decision based on the combination of large numbers and soft decision based on the confidence (maximum likelihood) combination are discussed. The single-bit hard decision algorithm, soft decision algorithm based on the maximum ratio combination, equal gain combination and selection combination, data fusion and decision algorithm based on evidence theory as well as softened 2bit hard combination and decision algorithm are mainly introduced, and detection performance and complexity are analyzed respectively.