Multiobjective cooperative spectrum sensing in cognitive radio using cat swarm optimization

Cognitive radio has emerged as a potential solution to the problem of spectrum scarcity. Cooperative spectrum sensing exploits the spatial diversity between cognitive radios for reliable detection of primary users' signals. The selection of weight and decision threshold for each cognitive radio can be formulated as a constrained multiobjective optimization problem where probabilities of false alarm and detection are the two conflicting objectives. This paper uses multiobjective cat swarm optimization in the field of cooperative spectrum sensing. The simulation results show that our proposed approach performs better in terms of efficient computation and quality of nondom-inating solutions.