|Table of Contents|

[1] Li Xi, Song Tiecheng, Zhang Yueyue, Chen Guojun, et al. A weighted selection combining schemefor cooperative spectrum prediction in cognitive radio networks [J]. Journal of Southeast University (English Edition), 2018, (3): 281-287. [doi:10.3969/j.issn.1003-7985.2018.03.001]
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A weighted selection combining schemefor cooperative spectrum prediction in cognitive radio networks()
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
Issue:
2018 3
Page:
281-287
Research Field:
Information and Communication Engineering
Publishing date:
2018-09-20

Info

Title:
A weighted selection combining schemefor cooperative spectrum prediction in cognitive radio networks
Author(s):
Li Xi Song Tiecheng Zhang Yueyue Chen Guojun Hu Jing
National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China
Keywords:
cognitive radio network cooperative spectrum prediction genetic algorithm-based neural network iterative self-organizing data analysis algorithm weighted selection combining
PACS:
TN915
DOI:
10.3969/j.issn.1003-7985.2018.03.001
Abstract:
A weighted selection combining(WSC)scheme is proposed to improve prediction accuracy for cooperative spectrum prediction in cognitive radio networks by exploiting spatial diversity. First, a genetic algorithm-based neural network(GANN)is designed to perform spectrum prediction in consideration of both the characteristics of the primary users(PU)and the effect of fading. Then, a fusion selection method based on the iterative self-organizing data analysis(ISODATA)algorithm is designed to select the best local predictors for combination. Additionally, a reliability-based weighted combination rule is proposed to make an accurate decision based on local prediction results considering the diversity of the predictors. Finally, a Gaussian approximation approach is employed to study the performance of the proposed WSC scheme, and the expressions of the global prediction precision and throughput enhancement are derived. Simulation results reveal that the proposed WSC scheme outperforms the other cooperative spectrum prediction schemes in terms of prediction accuracy, and can achieve significant throughput gain for cognitive radio networks.

References:

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Memo

Memo:
Biographies: Li Xi(1992—), female, graduate; Song Tiecheng(corresponding author), male, doctor, professor, songtc@seu.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.61771126, 61372104), the Science and Technology Project of State Grid Corporation of China(No.SGRIXTKJ[2015]349).
Citation: Li Xi, Song Tiecheng, Zhang Yueyue, et al. A weighted selection combining scheme for cooperative spectrum prediction in cognitive radio networks[J].Journal of Southeast University(English Edition), 2018, 34(3):281-287.DOI:10.3969/j.issn.1003-7985.2018.03.001.
Last Update: 2018-09-20