Cognitive Radio Parameter Adaptation Using Multi-objective Evolutionary Algorithm
Cognitive Radio (CR) is an intelligent Software Defined Radio (SDR) that can alter its transmission parameters according to predefined objectives by sensing the dynamic wireless environment. In this paper, we propose a method to determine the necessary transmission parameters for a multicarrier system based on multiple scenarios using a multi-objective evolutionary algorithm like Non-dominated Sorting based Genetic Algorithm (NSGA-II). Each scenario is represented by a fitness function and represented as a composite function of one or more radio parameters. We model the CR parameter adaptation problem as an unconstrained multi-objective optimization problem and then propose an algorithm to optimize the CR transmission parameters based on NSGA-II. We compute the fitness score by considering multiple scenarios at a time and then evolving the solution until optimal value is reached. The final results are represented as a set of optimal solutions referred as pareto-front for the given scenarios. We performed multi-objective optimization considering two objectives and the best individual fitness values which are obtained after final iteration are reported here as the pareto-front.
KeywordsCognitive Radio Modulation Index Cognitive Radio System Software Define Radio Symbol Rate
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