Resource Allocation by Fuzzy Based Cluster Using Greedy Algorithm for Secure Communication

Abstract

In cognitive Wireless Radio networks, information transfer and power transfer are given special consideration in next-generation wireless networking devices like Simultaneous Wireless Information and Power Transfer. The benefit of integrating cognitive network concepts is that it provides greater efficiency on energy and spectrum to address interference, fading, and path loss, among many other issues, in certain critical applications. Energy harvesting (EH) is a secure and cost-effective method of powering up cluster heads when needed. The proposed method considers two phases. The first phase is energy harvesting of SUs transferred in power signals send by the hybrid access point during wireless power transfer (WPT). While in the second phrase, Wireless Information Transfer (WIT) phase, the captured energy is used while simultaneously acquiring transmission possibilities. In addition, a fuzzy-based cluster using a greedy algorithm is used to reduce PU secrecy outages and to provide the best ideal result. These may be identified using a convolutional neural network (CNN) to detect and classify distinct attack types. This paper presents an efficient resource allocation using fuzzy logic-based clustering and greedy algorithms, which can provide better performance than other technologies. The subsystem for cognitive radio networks is configured, and the primary nodes’ secrecy is maintained and free of three attacks, and the results are simulated using MATLAB tools.