Research On Dynamic Spectrum Allocation Algorithm In Cognitive Wireless Network

With the rapid development of wireless communication technology,the demand for radio frequency spectrum resources in related fields has surged.However,radio frequency spectrum is a non-renewable resource,and the existing spectrum resources are becoming increasingly scarce and valuable.Most of the existing spectrum allocation strategies are static spectrum allocation,which can only ensure that authorized users have spectrum available,while non authorized users’ communication cannot be guaranteed,resulting in a large amount of idle spectrum resources being wasted and inefficient spectrum utilization.To address the shortage of spectrum resources in the field of wireless communication,scholars both domestically and internationally have utilized cognitive radio technology to study spectrum allocation problems and proposed a variety of classic dynamic spectrum allocation methods,such as improving spectrum utilization efficiency by allowing authorized and unauthorized users to share spectrum resources.Although relevant research has been helpful in solving the shortage of spectrum resources in the field of wireless communication,most current algorithm models still need improvement in terms of optimization accuracy and convergence speed.This paper focuses on optimizing existing classic algorithm models to effectively improve overall network efficiency and spectrum utilization efficiency.The specific work content is as follows:1.A spectrum allocation scheme based on graph coloring model and heuristic search algorithm is proposed to address the problem of spectrum resource scarcity in cognitive wireless networks.The graph coloring model is used to abstract the spectrum allocation problem into a topological structure diagram,representing the spectrum access and communication interference relationship between authorized and unauthorized users.To improve the optimization precision and convergence speed of current spectrum allocation algorithms,improve the three stages of the classic heuristic search algorithm-fireworks algorithm(explosion,mutation,and selection strategy)separately.Through simulation experiments,it was found that the network spectrum efficiency optimization results of the algorithm model proposed in this article have been improved by 12% compared to the traditional fireworks algorithm,which verifies its feasibility and effectiveness in optimization capability and network performance.2.With the aim of diversifying the practical application scenarios of spectrum expansion and further improving the total efficiency and utilization of spectrum in cognitive wireless networks,this study employs two classic non-cooperative game models in game theory-cournot game and Stackelberg game to investigate the spectrum allocation problem and construct a spectrum leasing model between primary and secondary users.For two different spectrum allocation scenarios,the signal-to-noise ratio parameter is introduced to differentiate the channel quality evaluation index of different spectra,and the relevant game models are optimized to achieve effective and rational allocation of spectrum resources in practical application scenarios.By seeking methods to satisfy the Nash equilibrium state of the two improved game models through theoretical derivation and simulation experiments,the optimal spectrum allocation strategy can be found to maximize the spectrum benefits obtained by the primary users.