A Novel Approach for Better QoS in Cognitive Radio Ad Hoc Networks Using Cat Optimization

Abstract

Cognitive Radio is a Wi-Fi verbal exchange methodology that allows the user to engage except having a fixed preassigned radio spectrum. Cognitive Radio Networks (CRNs) are having the routing hassle that is one of the serious constraints. Ad hoc networks are non-centralized Wi-Fi networks that can be constructed and there is no need for any preexisting infrastructure for these networks. Here every point can work as a router. In this paper, the authors have explained the Cognitive Radio Networks (CRN) that are obtaining so a whole lot of recognition where the principal focus is on the dynamic undertaking of channels to wireless devices. In this paper, cognitive radio networks are primarily focused. Nowadays, almost all the networks rely on fixed allocated networks in an approved or unapproved frequency group. In this paper literature evaluates associated to CRN and an optimization algorithm to enhance the overall performance of TE under CRN has been discussed. Swarm intelligence technique is used in the paper. Swarm approach is clearly the combination of the decentralized attribute to gain excellent viable solutions. The motivation regularly creates from nature, more often than non natural outlines. One of the effective approachs known as Cat swarm has been used to acquire high price of accuracy and much low error rates which improves the lifespan of the network. The results are carried out by the use of CSO (Cat Swarm Optimization) algorithm and parameters like energy consumption, congestion, overhead consumption, and number of routing rules are used to analyze the overall performance of the algorithm.