Research On Spectrum Allocation Strategy On Account Of Intelligent Algorithm

The 5G wireless communication technology is now rapidly developing.However,there are limitations in the optimization and utilization of wireless resources,and still cannot solve the contradiction between the limited spectrum resources and the rapid growth of the business needs.The emergence of cognitive wireless spectrum allocation technology has brought about new changes.Spectrum allocation technology can use the idle frequency bands without causing mutual interference at the same time.It makes full use of the wireless space resources and greatly improves the utilization of spectrum resources.This paper focuses on the spectrum allocation problem of intelligent algorithms in cognitive wireless networks.Given a limited spectrum and a set of users,we consider the maximum utility of the network and the fairness of all users in the network.In the context of the above approach,the main work completed in this article is as follows:(1)The graph theory coloring model is used to model the spectrum allocation problem in cognitive wireless networks.For the traditional spectrum allocation model,there are defects such as user fairness and unfair competition between users.In this paper,different cluster intelligent algorithms are used to optimize the spectrum allocation,so that the total system benefits and user fairness are better solved.(2)The new binary bat algorithm is applied to spectrum allocation optimization.Firstly,two random numbers are introduced in the frequency update to control the global and local balance.Secondly,a new discrete function is introduced to disperse the velocity to the position in the process of continuous space and discrete space conversion.Finally,the new binary bat algorithm and the traditional binary bat algorithm are compared with the goal of maximizing total system benefit and fairness of secondary user.(3)A symbiotic time-varying binary scorpion sheath algorithm is proposed and applied to the cognitive radio spectrum allocation.Firstly,a symbiotic strategy is introduced in the follower location to enhance development capabilities.Secondly,the time-variable function is introduced to disperse the position in the process of continuous space and discrete space conversion.The results show that the new binary bat algorithm and symbiotic and time-variable binary salp swarm algorithm is superior to other algorithms in the application and can be effectively and stably used for spectrum allocation optimization.