期刊
IEEE WIRELESS COMMUNICATIONS LETTERS
卷 8, 期 6, 页码 1727-1730出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LWC.2019.2939314
关键词
Spectrum sensing; SNR-wall; deep learning; cooperative detection
资金
- NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization [U1709219]
- National Natural Science Foundation of China [61922071, 61871344, 61725104]
In cognitive radio systems, the ability to accurately detect primary user's signal is essential to secondary user in order to utilize idle licensed spectrum. Conventional energy detector is a good choice for blind signal detection, while it suffers from the well-known SNR-wall due to noise uncertainty. In this letter, we firstly propose a deep learning based signal detector which exploits the underlying structural information of the modulated signals, and is shown to achieve the state of the art detection performance, requiring no prior knowledge about channel state information or background noise. In addition, the impacts of modulation scheme and sample length on performance are investigated. Finally, a deep learning based cooperative detection system is proposed, which is shown to provide substantial performance gain over conventional cooperative sensing methods.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据