Research On Resource Allocation Algorithm For Cognitive Radio Networks

In the era of "Internet +",with the development of Internet of Things,cloud computing and big data technology has led to the rapid growth of communication traffic and mobile data traffic,and the spectrum resources in wireless communication networks have become very scarce.In order to alleviate the increasingly tight supply and demand relationship of spectrum resources,cognitive radio technology has gradually become a hot issue.The cognitive radio networks can perceive and discover spectrum holes in the network environment,and adjust its own parameters according to the sensing result to adapt to the network environment and dynamically access the underutilized spectrum resources in the network to effectively improve the spectrum utilization and alleviate the tight supply and demand relationship of spectrum resources.Firstly,in this paper,we summarize the research background and significance of cognitive radio networks,and summarizes the relevant research and status at home and abroad.The key technologies and access mechanisms in cognitive radio networks are introduced in detail,and the economic theories and models that can be applied to cognitive radio networks and further improve system performance are introduced,including Game Theory models,Auction Theory models and Contract Theory model.Secondly,considering the influence of receiving terminal interference,we propose a full-interference system model based on the underlying mechanism,and proposes a joint strategy resources allocation algorithm based on the model.The joint strategy algorithm first performs channel allocation through a genetic algorithm based on directed mutation,and then performs power allocation within the channel through an auction algorithm.The simulation results show that the algorithm can effectively improve the system integration rate,ensure the fairness between secondary base stations,and converge to Nash Equilibrium at a faster speed.Finally,this paper models the spectrum allocation process of cognitive radio networks into a spectrum trading process under a monopoly market.The secondary base station acquires the service type information of different users through context aware,and establishes a stable bilateral matching between secondary base stations and users through the deffered acceptance algorithm in the Matching Theory.After that,the primary base station comprehensively considers the adverse selection and moral hazard based on the contract theory.Under the issue of risk,different down paymentinstallment payment contracts are provided according to the type of secondary base station to maximize the benefits of their own.The simulation proves that the method can effectively optimize system performance,improve spectrum utilization and the benefit of the primary base station.