SPECTRUM SENSING IN COGNITIVE RADIO NETWORK USING CUCKOO SEARCH WITH CHARGED SYSTEM SEARCH HEURISTIC

Abstract

The technology that is known as Cognitive Radio (CR) is an attractive answer to effectively allocate a radio spectrum among all the licensed Primary Users (PUs) and the Secondary Users (SUs) or the unlicensed. For making use of this channel or the spectrum, it is required to sense the channel to check for the PU presence, known as spectrum sensing. This is a crucial activity found in the CR scenario. A key problem of research for the Cognitive Radio Networks (CRNs) is spectrum allocation. The use of this CRN has to be maximized within the model of optimization. For solving the problem of combinatorial optimization effectively, there was a hybrid Cuckoo Search (CS) along with a Charged System Search (CSS) algorithm (the cuckoo-CSS) that was proposed for the reduction of the bandwidth and the reporting time while at the same time maintaining a particular sensing performance. In this work, the definition of a framework for the allocation of the spectrum within the CR systems has been described, and a new method with the hybrid cuckoo-CSS algorithm was employed to optimize the spectrum allocation. The simulation results prove that these solutions produced by the cuckoo-CSS algorithm were found to be better compared to the ones produced by the CSS or the single-CR.