Wideband spectrum sensing for cognitive radio networks: a survey
Durham University · King's College London · +2 more institutions
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Abstract
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.
Citation impact
591
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- FWCI
- 67.87
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- 100%
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Authors
4Topics & keywords
Topics
Keywords
- Cognitive radio
- Wideband
- Computer science
- Nyquist–Shannon sampling theorem
- Radio spectrum
- Compressed sensing
- Telecommunications
- Radio frequency
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