Weighted Hard Combination for Cooperative Spectrum Sensing under Noise Uncertainty

Ruyuan ZHANG  Yafeng ZHAN  Yukui PEI  Jianhua LU  

IEICE TRANSACTIONS on Communications   Vol.E97-B    No.2    pp.275-282
Publication Date: 2014/02/01
Online ISSN: 1745-1345
DOI: 10.1587/transcom.E97.B.275
Print ISSN: 0916-8516
Type of Manuscript: Special Section PAPER (Special Section on Technologies for Effective Utilization of Spectrum White Space)
cooperative spectrum sensing,  noise uncertainty,  hard combination,  energy detection,  

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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 one-out-of-N rule. As noise uncertainty is unavoidable, this algorithm is highly practical.