Evaluation of Energy Efficiency of Spectrum Sensing Algorithm for Cognitive Radio Networks

Cognitive Radio (CR) is a radio communications and networking technology that has attracted considerable interest from both academia and industrial sectors in recent times. As is well known, spectrum sensing forms the very backbone on which the operation of CR technology draws upon. Spectrum sensing can be defined as the task of collecting information regarding spectral resource utilization and presence of primary users (PU) in a given area; which can then be used to accommodate secondary users (SU) on a non interfering basis. Spectrum Sensing is one of the most power hungry tasks in a Cognitive Radio system. Due to the energy constraints of battery powered mobile terminals, energy efficiency emerges as a significant challenge in CR networks. However, there is a direct tradeoff between bandwidth efficiency and power efficiency according to Shannon's Channel Capacity Theorem. This paper describes an energy efficient two stage spectrum sensing algorithm that is based on joint energy detection and cyclostationary feature detection. The paper also evaluates the energy efficiency of the spectrum sensing algorithm for CR and it is shown through simulations that the scheme attempts to simultaneously achieve good power efficiency as well as bandwidth efficiency. It is also noted that the application of Compressed Sensing leads to further improvement in the energy efficiency of our algorithm.