Optimization of multiband sensing-time-adaptive detection in cognitive radio networks using artificial immune algorithm

Spectrum sensing is an important component of cognitive radio technology which enables secondary users to sense the environment and find the spectrum holes. In this study, a multiband sensing-time-adaptive framework is used for wideband spectrum sensing in order to maximize the aggregate throughput capacity of the cognitive radios and reduce their interference to the primary users. The optimization problem is non-convex, and convex optimization can solve the problem with restrictions. in this paper we use the artificial immune algorithm based on the clonal selection theory to obtain the optimal solutions without any reformulations or mathematical costs.