Enhanced fuzzy C-means clustering based cooperative spectrum sensing combined with multi-objective resource allocation approach for delay-aware CRNs

摘要

In cognitive radio networks (CRNs), the resource allocation is viewed as a multi-objective optimisation problem in terms of limitation of quality of service, the capacity of a channel and the transmitted power. To overcome these individual issues many researchers have been undertaken, but it does not solve the multi-objective problems. In this study, the authors propose a multi-objective random walk grey wolf optimisation (MORWGWO) algorithm to enhance the resource allocation in the CRNs. Here, they combined the spectrum sensing process with the resource allocation process. Initially, an enhanced fuzzy C-means algorithm based cluster formation is proposed for spectrum sensing and then they model the resource allocation process and propose a MORWGWO algorithm for CRNs which generates the Pareto front inbetween of different objectives in a time-efficient manner. The simulation result shows that the proposed method significantly enhances the network performance in terms of delay, delivery ratio, throughput, network lifetime, energy consumption, and fairness index. Result shows that the proposed method has a better throughput of 23.22, 15.09, 6.13% for varying nodes and 27.25, 10.62, 7.09% for varying data transfer rates while comparing with the multiple objective particle swarm optimisation, non-dominated sorting genetic algorithm, and multi-objective evolutionary algorithm.