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Title:
"Soft decision" spectrum prediction based on back-propagation neural networks
Author: Bai, Suya (1) ; Zhou, Xin (1) ; Xu, Fanjiang (1)
Conference Name: 2014 IEEE International Conference on Computing, Management and Telecommunications, ComManTel 2014
Conference Date: April 27, 2014 - April 29, 2014
Issued Date: 2014
Conference Place: Da Nang, Viet nam
Publish Place: IEEE Computer Society
Indexed Type: EI
ISBN: 9781479929030
Department: (1) Science and Technology on Integrated Information System Laboratory, Institute of Software Chinese Academy of Sciences, Beijing, China
Abstract: In the cognitive radio system, spectrum prediction attracts more and more attention, which predicts future spectrum holes to save energy of spectrum sensing and to improve the efficiency of spectrum access. The current research on spectrum prediction is similar to the hard decision in the communication system. However, the hard decision loses amount of channel information during the process of obtaining channel statuses, which decreases the predictive accuracy of spectrum prediction. Therefore, we propose a "soft decision" model for spectrum prediction based on back-propagation neural networks. In the proposed model, the power values of frequency sampling point instead of the channel status are used as the inputs of the spectrum prediction model. Our experimental results demonstrate that the predictive accuracy of the proposed "soft decision" spectrum prediction model is better than the performance of conventional "hard decision". © 2014 IEEE.
English Abstract: In the cognitive radio system, spectrum prediction attracts more and more attention, which predicts future spectrum holes to save energy of spectrum sensing and to improve the efficiency of spectrum access. The current research on spectrum prediction is similar to the hard decision in the communication system. However, the hard decision loses amount of channel information during the process of obtaining channel statuses, which decreases the predictive accuracy of spectrum prediction. Therefore, we propose a "soft decision" model for spectrum prediction based on back-propagation neural networks. In the proposed model, the power values of frequency sampling point instead of the channel status are used as the inputs of the spectrum prediction model. Our experimental results demonstrate that the predictive accuracy of the proposed "soft decision" spectrum prediction model is better than the performance of conventional "hard decision". © 2014 IEEE.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/16638
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Bai, Suya ,Zhou, Xin ,Xu, Fanjiang . "Soft decision" spectrum prediction based on back-propagation neural networks[C]. 见:2014 IEEE International Conference on Computing, Management and Telecommunications, ComManTel 2014. Da Nang, Viet nam. April 27, 2014 - April 29, 2014.
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