Resource Allocation in Cognitive Radio Networks Based on Modified Ant Colony Optimization

Abstract

Cognitive Radio Network (CRN) is a set of a heterogeneous network that comprises the number of the users dynamically accessing the spectrum. A major issue in cognitive radio network is related to the resource channel allocation for the users in the network environment where the impact of unreliable resource allocation may lead to the increase of interference among the users. In this paper, we proposed the solution of resource allocation for cognitive radio network using the modified Ant Colony Algorithm - a metaheuristic approximation inspired from the behavior of the colony of ants in foraging. Our proposed solution relies on the pheromone intensity in the path used by ants to make decision of the channel selection. The objective is to obtain the optimal solution of channel allocation by Cognitive Radio Users. From manual validation using MS Excel, the result showed that the ants could improve the channel allocation and attain the fairness in the Cognitive Radio environment, and then the throughput is increased.