| 基于监督学习的协作宽带压缩频谱检测方案 |
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| 引用本文： | 马彬,王宏明,谢显中.基于监督学习的协作宽带压缩频谱检测方案[J].电子学报,2000,48(12):2338-2344. |
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| 作者姓名： | 马彬 王宏明 谢显中 |
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| 作者单位： | 1. 重庆邮电大学移动通信技术重庆市重点实验室, 重庆 400065;
2. 重庆邮电大学通信与信息工程学院, 重庆 400065 |
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| 摘 要： | 宽带压缩频谱检测存在信号稀疏度未知和次用户检测开销过大的问题.因此，本文提出一种高效的协作宽带压缩频谱检测方案.首先，推导了一种基于学习的稀疏度自适应预测模型.其次，设计了一种宽带频谱筛选算法.最后，提出一种协作宽带压缩频谱检测方案.仿真结果表明，自适应预测模型的拟合效果优于现有预测模型，并且所提检测方案也有效地降低了次用户采样率和频谱重构时延.
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| 关 键 词： | 宽带频谱检测 协作检测 压缩感知 稀疏度估计 监督学习 |
| 收稿时间： | 2019-12-02 |
A Collaborative Wideband Compressed Spectrum Sensing Scheme Based on Supervised Learning |
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| MA Bin,WANG Hong-ming,XIE Xian-zhong.A Collaborative Wideband Compressed Spectrum Sensing Scheme Based on Supervised Learning[J].Acta Electronica Sinica,2000,48(12):2338-2344. |
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| Authors: | MA Bin WANG Hong-ming XIE Xian-zhong |
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| Affiliation: | 1. Chongqing Key Laboratory of Mobile Communications Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;
2. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China |
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| Abstract: | Wideband compressed spectrum sensing has the problems of unknown signal sparsity and high overhead of secondary users sensing.Therefore,this paper proposed an efficient cooperative scheme of wideband compressed spectrum sensing.Firstly,based on learning,a sparsity adaptive learning prediction model was derived.Secondly,a wideband spectrum filtering algorithm is designed.Finally,a cooperative wideband compressed spectrum sensing scheme was proposed.The simulation results show that the fitting effect of the adaptive prediction model are better than the existing prediction model,and the proposed sensing scheme effectively reduces the sampling rate and spectrum reconstruction delay of secondary users. |
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| Keywords: | wideband spectrum sensing collaborative sensing compressed sensing sparsity estimation supervised learning |
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