Abstract

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, also called cognitive users (CUs), 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 initial step in cognitive transmission is called spectrum sensing. In spectrum sensing, a CU senses the spectrum in order to detect the activity of the licensed users. Spectrum sensing is usually accomplished cooperatively in order to improve the reliability of its results. In cooperative spectrum sensing (CSS), individual sensing results should be exchanged in order to make a global decision regarding spectrum occupancy. Thus, CSS consumes a significant a mount of energy, representing a challenge for CUs. Moreover, the periodicity of CSS and increasing the number of channels to be sensed complicates the problem. To this end, energy efficiency in CSS has gained an increasing attention recently. In this dissertation, a number of energy-efficient algorithms/schemes for CSS is proposed. The proposed works include energy efficient solutions for low energy consumption in local sensing stage, results’ reporting stage and decision-making stage. The proposed works are evaluated in terms of the achievable energy efficiency and detection accuracy, where they show a significant improvement compared to the state-of-the-art proposals. Moreover, a comprehensive energy-efficient approaches are proposed by combining different algorithms presented in this dissertation. These comprehensive approaches aim at proving the consistency of the proposed algorithms to each other and maximizing the achievable energy efficiency in the whole CSS process. Moreover, high energy consumption is not the only challenge of CSS. Another important problem in CSS is the vulnerability of the security risks which can effectively degrade the energy efficiency of cognitive radio networks. In this dissertation, we propose three different strategies against security attackers. Specifically, authentication protocol for outsider attackers, elimination algorithm for insider attackers, and a punishment policy are presented in this dissertation. While designing these strategies, an eye is kept on energy efficiency such that increasing immunity against attacker does not affect energy efficiency. Therefore, the tradeoff between energy efficiency and security in CSS has been achieved.