"Soft decision" spectrum prediction based on back-propagation neural networks
文献类型：会议论文
| 作者 | Bai, Suya (1) ; Zhou, Xin (1) ; Xu, Fanjiang (1) |
| 出版日期 | 2014 |
| 会议名称 | 2014 IEEE International Conference on Computing, Management and Telecommunications, ComManTel 2014 |
| 会议日期 | April 27, 2014 - April 29, 2014 |
| 会议地点 | Da Nang, Viet nam |
| 页码 | 128-133 |
| 中文摘要 | 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. |
| 英文摘要 | 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. |
| 收录类别 | EI |
| 会议录出版地 | IEEE Computer Society |
| 语种 | 英语 |
| ISBN号 | 9781479929030 |
| 源URL | [http://ir.iscas.ac.cn/handle/311060/16638]  |
| 专题 | 软件研究所_软件所图书馆_会议论文 |
| 推荐引用方式 GB/T 7714 | 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. |
入库方式： OAI收割
来源：软件研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。