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Cognitive radio has been proposed as a promising technology to resolve the spectrum scarcity problem by dynamically exploiting underutilized spectrum bands. Cognitive radio technology allows unlicensed users to exploit the spectrum vacancies at any time with no or limited extra interference at the licensed users. Usually, cognitive radios create networks in order to better identify spectrum vacancies, avoid resultant interference, and consequently, magnify their revenues. One of the main challenges in cognitive radio networks is the high energy consumption, which may limit their implementation especially in battery-powered terminals. The large consumption mainly occurs during the spectrum sensing stage, especially if a cooperative approach is employed, and has an impact on the data transmission stage. Many algorithms have been proposed in the literature in order to improve the energy efficiency of cooperative spectrum sensing methods in cognitive radio networks. In this article, we provide an overview of state-of-the-art research that addresses this problem. Furthermore, we suggest important design guidelines of an energy-efficient framework for cooperative spectrum sensing.

Cooperative spectrum sensing (CSS) represents a key factor in the success of cognitive radio networks. CSS implies that users report their local sensing results to a fusion center in order to process them. The two popular reporting schemes are soft and hard schemes. In hard scheme, local sensing result is conveyed by a single bit, whereas the sensing result is reported as it is in the soft scheme. The more detection accuracy attained by soft scheme is confronted by more resource efficiency in hard scheme. This paper provides analytic comparison between both schemes in terms of throughput, energy consumption and energy efficiency. Our work includes deriving the sufficient conditions on the frame length by which the hard scheme outperforms soft scheme for each comparison aspect. Our results show that hard scheme always achieves higher throughput, while, at short frames and large number of users, it consumes less energy and attains higher energy efficiency.

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