Chaotic Equilibrium Optimization Algorithm Based Cooperative Spectrum Sensing and Energy Efficient Cognitive Radio Networks

The need for wireless communication in the present and the future is for green communication. The cognitive radio network must meet the requirements for green communication in order to be the next-generation communication network. So improving energy efficiency is a must for the development of cognitive radio networks. However, sensor performance must be reduced in order to improve energy efficiency. In order to consider the two key indicators of sensing performance and energy efficiency, this research suggests a Chaotic Equilibrium Optimization (CEO) method that may effectively boost energy efficiency while enhancing spectrum sensing performance. The algorithm first learns the initial reliability value of the nodes by training, sorts them based on highest reliability, selects an even number of nodes with highest reliability, divides the chosen nodes into two groups, and then alternates the operation of the two groups of nodes. While they wait for additional instructions from the fusion center, the other nodes that are not now participating in cooperative spectrum sensing are in a state of silence. Experimental demonstrations are effectuated and analyzed the performances of the performances of the proposed work. The proposed work effectively senses the spectrum than the other approaches.