Research And Optimization Of Spectrum Allocation In Cognitive Radio System

With the rapid rise of the wireless communication industry and the emergence of various new business,the network operating environment is more complex and changeable,and the phenomenon of the shortage of radio spectrum resource is becoming more and more obvious.In view of the above situation,the concept of cognitive radio can be reasonable and effective to solve the problem.People want to use the cognitive radio technology to effectively improve the utilization of radio spectrum resources and achieve flexible allocation of spectrum.The spectrum allocation scheme in cognitive radio system is mainly in the implementation among the various primary users and secondary users.Under the condition that the primary users won't be influenced by the unbearable interference,cognitive users can use the licensed spectrum optionally.This method can reduce the spectrum holes in the whole system,so as to improve the utilization of spectrum resources.This thesis researches the optimization and application of spectrum allocation algorithm.Firstly,this paper describes the background knowledge and related concepts of cognitive radio,and then discusses several key technologies of cognitive radio system including spectrum sharing,spectrum management and spectrum allocation.Then,the main work of this thesis is discussed in detail.First is proposing the genetic ant colony optimization(GACO)algorithm with the genetic algorithm and ant colony algorithm are fused by adopting new convergence strategy to have complementary advantages.Second is proposing binary self-adaptive step glowworm swarm optimization(BAGSO)algorithm which is based on the strong convergence ability of the basic glowworm swarm optimization(GSO)algorithm.The two parts of genetic algorithm and ant colony algorithm in the GACO algorithm has been optimized.The chromosomes in the genetic algorithm can carry the information of the two aspects of cognitive users and authorized spectrum.The running results of genetic algorithm can be transferred to the initial pheromone distribution of the ant colony algorithm.And the ant colony algorithm can converge in the framework of bigraph quickly to achieve the optimal solution.Simulation experiments show that GACO algorithm can improve the overall satisfaction of the network in the spectrum allocation better than the color sensitive graph coloring algorithm(CSGC).BAGSO algorithm encodes the spatial location of the glowworm in binary type,in order to enhance the global exploration and stability of the algorithm.Through the experiment of obtaining the extreme value of multi-peak function,it is shown that the BAGSO algorithm is better than GSO and self-adaptive step glowworm swarm optimization(AGSO)algorithm in terms of searching ability.When the BAGSO algorithm is applied to the spectrum allocation,each glowworm represents an allocation scheme,and the change of its position maps the adjustment of allocation scheme.The simulation experiments show that the performance of the spectrum allocation based on BAGSO algorithm is obviously superior to the spectrum allocation based on CSGC algorithm.