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Weighted Hard Combination for Cooperative Spectrum Sensing under Noise Uncertainty
Ruyuan ZHANG Yafeng ZHAN Yukui PEI Jianhua LU
Publication
IEICE TRANSACTIONS on Communications
Vol.E97B
No.2
pp.275282 Publication Date: 2014/02/01 Online ISSN: 17451345
DOI: 10.1587/transcom.E97.B.275 Print ISSN: 09168516 Type of Manuscript: Special Section PAPER (Special Section on Technologies for Effective Utilization of Spectrum White Space) Category: Keyword: cooperative spectrum sensing, noise uncertainty, hard combination, energy detection,
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Summary:
Cooperative spectrum sensing is an effective approach that utilizes spatial diversity gain to improve detection performance. Most studies assume that the background noise is exactly known. However, this is not realistic because of noise uncertainty which will significantly degrade the performance. A novel weighted hard combination algorithm with two thresholds is proposed by dividing the whole range of the local test statistic into three regions called the presence, uncertainty and absence regions, instead of the conventional two regions. The final decision is made by weighted combination at the common receiver. The key innovation is the full utilization of the information contained in the uncertainty region. It is worth pointing out that the weight coefficient and the local target false alarm probability, which determines the two thresholds, are also optimized to minimize the total error rate. Numerical results show this algorithm can significantly improve the detection performance, and is more robust to noise uncertainty than the existing algorithms. Furthermore, the performance of this algorithm is not sensitive to the local target false alarm probability at low SNR. Under sufficiently high SNR condition, this algorithm reduces to the improved oneoutofN rule. As noise uncertainty is unavoidable, this algorithm is highly practical.


