Optimal spectrum and power allocation using evolutionary algorithms for cognitive radio networks

Cognitive radio is a promising technology for efficient spectrum utilization. It explores dynamic spectrum access features while satisfying interference constraints. In this work, a joint power and spectrum allocation algorithm is proposed to maximize the cognitive network throughput while satisfying interference constraints of both primary and secondary users in the network. Evolutionary algorithms are used to solve the joint power and spectrum allocation problem. Furthermore, the algorithmic performance is compared in terms of quality of solution. And also we optimized the maximum utilization of the network and capacity of each user simultaneously by using Multi-Objective Differential Evolution (MODE) and Nondominated Sorting Genetic Algorithm II (NSGA-II). Simulation results show that the pareto optimal fronts provide the trade-off solutions between total network utilization and individual sum capacity of user.