Research And Application Of Cognitive Radio Spectrum Allocation Method Based On Swarm Intelligence

With the advent of new wireless communication technologies,the scarcity of spectrum resources and the low efficiency of authorized spectrum have become a reason to the development of wireless communication technology,cognitive radio technology is developed in such a context.It is a dynamic access spectrum communication mode,can discover and use the idle spectrum,thus achieve the purpose of improving communication efficiency.The emergence of cognitive radio provides an effective solution to the shortage of spectrum resources,therefore,the research on cognitive radio technology has very important research significance and application prospect.In this paper,the main link of cognitive radio--spectrum allocation is studied in depth.The main research contents are as follows:(1)First of all,understand the basic theory of cognitive radio technology.At the same time,the commonly used spectrum allocation model is analyzed,and the graph coloring model is established as the basis of this paper.Secondly,the basic theory and application of swarm intelligence algorithm are understood.Because of its simple implementation and strong search ability,swarm intelligence algorithm has been used in cognitive radio optimization problems,and has obtained some research results.(2)In cognitive radio,the spectrum allocation problem can be described as a set of optimization problems which satisfy the constraint conditions,and belongs to the complex optimization problem..In order to verify the superiority of the swarm intelligence algorithm in solving the spectrum allocation problem,this paper compares the spectrum allocation method based on the swarm intelligence algorithm with the classical color sensitive graph theory coloring method.The experimental results show that the swarm intelligence algorithm is effective in spectrum allocation problem,and the optimization performance is better than the classical color sensitive graph theory coloring method.(3)Swarm intelligence algorithm is a concept inspired by the social behavior of biological populations in nature.Some parameters involved in the algorithm are usually set according to certain experience,which reduces the optimization ability of the algorithm to a certain extent.In this paper,an adaptive quantum genetic algorithm is proposed,in the process of population evolution,the excellent individuals in each generation are directly inherited to the next iteration to ensure that the excellent individuals in the population will not be eliminated in the evolution process.When an individual is updated with a quantum rotation gate,the rotation angle varies with the evolution of the population.To further improve the optimization performance of the improved algorithm,this paper also introduces the idea of individual mutation in the algorithm.When the individual satisfies the variation condition,the quantum non-gate is used to mutate the individual.Finally,the validity of the proposed algorithm is verified by testing the complex function.(4)The application of adaptive quantum genetic algorithm in spectrum allocation problem is studied.The adaptive quantum genetic algorithm is applied to solve the spectrum allocation problem,the static and dynamic test experiments of spectrum allocation are used to verify the effectiveness of the algorithm in solving the spectrum allocation problem.,and compared with the basic quantum genetic algorithm,genetic algorithm and particle swarm optimization algorithm to verify its superiority.From the simulation test results,we can see that compared with the other three algorithms,the adaptive quantum genetic algorithm is more suitable to solve the spectrum allocation problem,the convergence speed of the algorithm is faster,the performance of optimization is better and better spectrum allocation schemes can be obtained.