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Energy-efficient cooperative spectrum sensing schemes for cognitive radio networks

Zhao, N.; Yu, Fei R.; Sun, Hongjian; Arumugam, Nallanathan

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N. Zhao

Fei R. Yu

Nallanathan Arumugam


Rapidly rising energy costs and increasingly rigid environmental standards have led to an emerging trend of addressing “energy efficiency” aspect of wireless communication technologies. Cognitive radio can play an important role in improving energy efficiency in wireless networks, because from the green perspective, spectrum is a natural resource which should not be wasted but be shared. In this article, we propose two energy-efficient and time-saving one-bit cooperative spectrum sensing schemes, which have two stages in the spectrum sensing process. If the signal-to-noise ratio is high or no primary user exists, only one stage of coarse spectrum sensing is needed, by which the sensing time and energy are saved. Otherwise, the second stage of fine spectrum sensing will be performed to increase the spectrum sensing accuracy. Furthermore, only one-bit decision is sent by each secondary user to minimize the overhead. The second proposed algorithm fully utilizes the local decisions of the coarse detection, and its energy consumption is further reduced with its sensing performance close to the first one. Plenty of simulation is performed, and the results show that the sensing time and energy consumption are both reduced significantly in the proposed schemes.


Zhao, N., Yu, F. R., Sun, H., & Arumugam, N. (2013). Energy-efficient cooperative spectrum sensing schemes for cognitive radio networks. EURASIP Journal on Wireless Communications and Networking, 2013, Article 120.

Journal Article Type Article
Acceptance Date Mar 19, 2013
Publication Date May 3, 2013
Deposit Date May 1, 2013
Publicly Available Date Oct 29, 2015
Journal EURASIP journal on wireless communications and networking.
Print ISSN 1687-1472
Publisher SpringerOpen
Peer Reviewed Peer Reviewed
Volume 2013
Article Number 120
Keywords Cognitive radio, Cooperative spectrum sensing, Energy efficiency.


Published Journal Article (675 Kb)

Publisher Licence URL

Copyright Statement
© 2013 Zhao et al.; licensee Springer. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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