Abstract
Cognitive radio (CR) is the new era of wireless technology having objective is to effective utilization of available spectrum. The primary function of cognitive radio is to sense the available free spectrum. The effectiveness of cooperative spectrum sensing (CSS) for searching available free spectrums in network of cognitive radio (CR) has been executed by receiving sensing data from surrounding node which is called CR. The data senses by CR node are transmitted at the central/common node named fusion center using either soft combining techniques or standard hard combining technique. These two combining techniques have a trade-off between performance and data required to sense the channel. The primary factor that decides the quality of sensing spectrum depends on weightage given to the coefficient used in softened data combing strategy in CSS. In this paper, optimal sensing framework using MultiObjective JAYA (MOJAYA) algorithm is presented which use optimality criterion of the Neyman-Pearson, as an effective tool to search the optimal coefficients vector so that sensing quality is preserved with less overhead. The performance of the presented framework which is based MOJAYA algorithm is thoroughly evaluated and compared with a conventional soft combining strategy as well as hard combining by using computer for simulation. The results show that the presented MOJAYA based performance is almost near to the conventional soft combining scheme i.e., equal gain combiner (EGC) with less overhead and bandwidth, which confirms the validation of presented framework.
Keywords: Cognitive Radio, Cooperative Sensing, Hard Combination, Multi-Objective JAYA, Soft Combination.