Adaptive sub-optimal energy detection based wideband spectrum sensing for cognitive radios

A Cognitive radio (CR) observes the environment through a combination of inputs from physical and MAC as well as user needs. These measureable parameters are usually referred as “meters”. Meters can provide the CR with an information base upon which to make decisions. Spectrum sensing is one of the most challenging issues in cognitive radio systems. Several algorithms and techniques to improve them are proposed in the context of spectrum sensing up to now but there is still remaining concerns about maintaining both accuracy and complexity conditions (as two important conditions of a spectrum sensing algorithm) in such algorithms. In this paper we proposed adaptive sub-optimal energy detection based algorithm for detection of the unused frequency bands and utilized part of the frequency axis. By choosing an appropriate threshold value (according to the channel noise), interference (between the primary and secondary users) in the proposed method can be reduced almost to zero and in this case it is an optimized approach. Moreover, the selection of the energy threshold in all energy detection based spectrum sensing methods is a major point of concern. Most of those algorithms are sensitive to the threshold value but our proposed algorithm is noticeably less sensitive to the selection of the energy threshold. Both theoretical analysis and simulation results prove the superiority of the proposed method versus the other state of the art methods. Our algorithm has an acceptable complexity as well as outstanding performance.