Hybrid whale optimisation algorithm for energy efficient cognitive radio network

The general use of wireless sensor devices and their importance in terms of deployment cost, size and user-friendliness have given an increase to many different applications of cognitive radio networks. In cognitive radio networks, energy efficiency is a very important problem. In the literature, many different methods are developed by researchers which are not able to produce the best results. Hence, in this article, a hybrid technique is developed to attain 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 are developed. The hybrid WOFA algorithm can be a combination of the Whale Optimization Algorithm (WOA) and Firefly Algorithm (FA). In the WOA algorithm, updating positions of the whales are achieved with the utilisation 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 analysed with the two different cases such as the target SINR ratio condition of 3.52 dB and the target SINR ratio condition of 5.11 dB.