Improved Cuckoo Search Algorithm For Spectrum Sensing In Sparse Satellite Cognitive Systems

We study the improved cuckoo search algorithm to promote the capability of spectrum sensing in satellite cognitive systems in this paper. We consider the application scenario of satellite network, which has relatively concise structures and flexible networking modes. The sharable frequency bands are divided into a number of subchannels, and cognitive users should discover unoccupied channels to access. In this case, the actual utilization of the spectrum is sparse as well as the changes in spectrum usage, so we propose an improved cuckoo search algorithm that adjusts dynamically the step size and switching/discovery probability in order to avoid redundant search and increase the convergence rate. Furthermore, we use simulations to study the performance of our proposed algorithm, which show the proposed scheme is noticeably efficient compared with the sequential search and a cuckoo search scheme with fixed step size and switching/discovery probability.