Energy-Efficient Cooperative Spectrum Sensing for Cognitive Radio Networks

Energy-Efficient Cooperative Spectrum Sensing for Cognitive Radio Networks

Saud Althunibat, Sandeep Narayanan, Marco Di Renzo, Fabrizio Granelli
ISBN13: 9781466665712|ISBN10: 1466665718|EISBN13: 9781466665729
DOI: 10.4018/978-1-4666-6571-2.ch004
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MLA

Althunibat, Saud, et al. "Energy-Efficient Cooperative Spectrum Sensing for Cognitive Radio Networks." Handbook of Research on Software-Defined and Cognitive Radio Technologies for Dynamic Spectrum Management, edited by Naima Kaabouch and Wen-Chen Hu, IGI Global, 2015, pp. 100-121. https://doi.org/10.4018/978-1-4666-6571-2.ch004

APA

Althunibat, S., Narayanan, S., Di Renzo, M., & Granelli, F. (2015). Energy-Efficient Cooperative Spectrum Sensing for Cognitive Radio Networks. In N. Kaabouch & W. Hu (Eds.), Handbook of Research on Software-Defined and Cognitive Radio Technologies for Dynamic Spectrum Management (pp. 100-121). IGI Global. https://doi.org/10.4018/978-1-4666-6571-2.ch004

Chicago

Althunibat, Saud, et al. "Energy-Efficient Cooperative Spectrum Sensing for Cognitive Radio Networks." In Handbook of Research on Software-Defined and Cognitive Radio Technologies for Dynamic Spectrum Management, edited by Naima Kaabouch and Wen-Chen Hu, 100-121. Hershey, PA: IGI Global, 2015. https://doi.org/10.4018/978-1-4666-6571-2.ch004

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Abstract

One of the main problems of Cooperative Spectrum Sensing (CSS) in cognitive radio networks is the high energy consumption. Energy is consumed while sensing the spectrum and reporting the results to the fusion centre. In this chapter, a novel partial CSS is proposed. The main concern is to reduce the energy consumption by limiting the number of participating users in CSS. Particularly, each user individually makes the participation decision. The energy consumption in a CSS round is expected by the user itself and compared to a predefined threshold. The corresponding user will participate only if the expected amount of energy consumed is less than the participation threshold. The chapter includes optimizing the participation threshold for energy efficiency maximization. The simulation results show a significant reduction in the energy consumed compared to the conventional CSS approach.

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