Hybrid Whale Optimization Algorithm for Energy Efficient Cognitive Radio Network

Abstract

The general use of wireless sensor devices and their importance in terms of deployment cost, size, and user friendly have given an increase to many different applications of cognitive radio networks. In cognitive radio networks, energy efficiency is a very important problem. In literature, many different methods are developed by researchers which are not able to produce the best results. Hence in this paper, a hybrid technique is developed to attain the energy efficiency deliberation intended for properly maintaining objective signal to interference plus noise ratio (SINR) need for the received interferences and cognitive users at a receiver of primary under a reference value. In the proposed methodology, interference threshold protection margin and protection factor to the SINR target is developed. The hybrid WOFA algorithm can be a mixing of the Whale Optimization Algorithm (WOA) and Firefly Algorithm (FA). In the WOA algorithm, updating positions of the whales are achieved with the utilization of the FA algorithm. The proposed method is designed in the MATLAB platform and it is compared with the existing approaches of WOA by robustness in addition to energy efficiency under the disturbance of channel gain. The proposed method is analyzed with the two different cases such as Target SINR ratio condition is 3.52dB and Target SINR ratio condition is 5.11dB respectively.