Research On Algorithm Of Spectrum Resource Allocation For Cognitive Radio Based On Energy Harvesting

With the development of the Internet,the demand for communication services,especially wireless communication services,is growing rapidly.Moreover,to wireless communication systems,their needs for spectrum resources are also increasing constantly.However,the traditional spectrum allocation policy determines that the spectrum cannot be efficiently allocated,which further leads to a shortage of spectrum resources.Cognitive radio is considered to be the most promising technology to solve the problem of wireless spectrum shortage.This technology uses various sensing methods to detect the idle spectrum that is not used by the primary user.Cognitive radio system is allowed to reuse the idle spectrum without affecting the normal transmission of data by the primary user.In this way,the dynamic allocation of the spectrum can be realized.And the purpose of improving the utilization rate of spectrum resources is achieved.The complex environment of cognitive radio equipment communication determines that its energy supply will be limited.And the problem of energy supply will directly affect the communication quality and survival of wireless devices.Therefore,the application of energy harvesting technology to cognitive radio has very important practical significance.Spectrum allocation is proved to be an NP-hard problem,which cannot be solved by precise mathematical methods.But this kind of problem can be solved very well by an intelligent optimization algorithm.Aiming at the spectrum allocation problem of cognitive radio based on energy harvesting and the optimization of spectrum allocation,the main work of this paper is as follows:(1)Aiming at the problem of spectrum allocation model,two common spectrum allocation algorithms based on graph theory are studied in this paper.The two models are the list coloring algorithm and the color-sensitive graph coloring algorithm.And the two algorithms are compared by simulation.In the list coloring algorithm,the distributed greedy algorithm and the distributed fair algorithm are compared.The simulation compares the fairness of spectrum allocation and system benefits of the two algorithms in different situations.In the color-sensitive graph theory coloring algorithm,cooperative and non-cooperative algorithms are compared.The simulation compares the system benefits of the two algorithms under different objective functions.The final simulation verifies the respective superiority of different algorithms in different goals.(2)The problem that the optimization algorithm is easy to stop during the optimization process is improved.Particle swarm optimization is selected as the solution algorithm.The particle swarm optimization algorithm is improved.According to the influence of inertia weight on particle velocity,population evolution speed and population aggregation degree are defined.Then it is combined with the inverse S function to improve the inertia weight.Through several test functions,the results show that the improved algorithm is superior to the original algorithm.(3)The spectrum allocation problem of cognitive radio based on energy harvesting is improved.By analyzing the cognitive radio based on energy harvesting,the maximum benefit of cognitive users in a single spectrum is taken into consideration in the priority of spectrum allocation.And the dormancy characteristic of cognitive radio base on energy harvesting is integrated into the priority.A spectrum priority assignment algorithm based on a single spectrum maximum benefit and cognitive radio sleep probability is proposed.Simulation results show that the improved spectrum allocation algorithm improves the spectrum utilization of cognitive radio.