WIDEBAND SPECTRUM SENSING FOR COGNITIVE RADIO NETWORKS: A SURVEY
WIDEBAND SPECTRUM SENSING FOR COGNITIVE RADIO NETWORKS: A SURVEY
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DOI：
10.1109/mwc.2013.6507397
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发表时间：
2013-04-01
影响因子：
12.9
通讯作者：
Chen, Yunfei
中科院分区：
文献类型：
--
作者：
Sun, Hongjian;Nallanathan, Arumugam;Chen, Yunfei
认知无线电已经成为下一代蜂窝网络中提高频谱利用率的最有前途的候选解决方案之一。未来认知无线电网络的一个关键要求是宽带频谱感知：次级用户在很宽的频率范围内可靠地检测频谱机会。在本文中，各种宽带频谱感知算法，连同讨论的优点和缺点的每种算法和挑战性的问题。特别注意的是使用的子奈奎斯特技术，包括压缩传感和多通道子奈奎斯特采样技术。
Cognitive radio has emerged as one of the most promising candidate solutions to improve spectrum utilization in next generation cellular networks. A crucial requirement for future cognitive radio networks is wideband spectrum sensing: secondary users reliably detect spectral opportunities across a wide frequency range. In this article, various wideband spectrum sensing algorithms are presented, together with a discussion of the pros and cons of each algorithm and the challenging issues. Special attention is paid to the use of sub-Nyquist techniques, including compressive sensing and multichannel sub-Nyquist sampling techniques.