Dynamic Spectrum Access Mechanism Design Based On Channel Recommendation

With the rapid development of communication technology,wireless communication services have grown rapidly,and global mobile data traffic has skyrocketed.Behind the prosperity of the wireless communication market,there is a hidden danger that cannot be ignored-spectrum resources are scarce.Wireless spectrum resources are limited and non-renewable.When the the most of spectrum is allocated,the spectrum resources will enter a shortage state,which will greatly limit the development of wireless communication services,but cognitive radio technology can effectively solve this problem.Most of the measurements show that the existing spectrum utilization is not high enough,and dynamic spectrum access technology can effectively improve spectrum utilization and solve the problem of lacking of spectrum.The basis of dynamic spectrum access is the sensing of spectrum information.The existing research on spectrum sensing have more or less problems such as low accuracy,difficulty in deployment,and large system overhead.In order to solve these problems,a channel recommendation model based on secondary user spectrum channel sensing information sharing is proposed,and the optimal channel selection strategy under the channel recommendation model is considered,and incentive mechanism is designed to encourage the secondary users to voluntarily join the channel recommendation system.Based on the research of recommended optimal channel selection strategies,the scenario of cognitive radio network where secondary users can share the information of channels is considered.In order to improve the system throughput,the channel is modeled as a two-state Markov process based on the proposed static channel selection strategy,and the system is modeled as a Markov decision process based on the dynamic channel selection strategy.The problem is transformed into the solving of the value function of the Markov decision process and the prove of the existence of the optimal solution.In order to solve the problem that the solution made by the traditional method can not converge to the optimal solution of the Markov decision process with continuous action space,a MRAS(Model Reference Adaptive Search)based method is proposed to get the optimal channel selection strategy.Based on the optimal recommendation based channel selection strategy,different channel selection strategies are analyzed and compared,and the good performance of the optimal channel selection strategy is verified.Based on the research of the recommended optimal channel selection strategy,the incentive mechanism in the above model is furth er studied here.In order to motivate secondary users to actively send out channel recommendation information,a reputation-based channel recommendation game model and a money-based channel recommendation game model are proposed,and the equilibrium analysis of the two game models are made.In the money-based channel recommendation game model,the price factor is introduced to adjust the controllability of the system equilibrium.Based on this,the effectiveness of the incentive mechanism is verified through simulation.In summary,a new model and incentive method for recommendation-based channel selection strategy and incentive mechan ism is proposed,and the optimization of static and dynamic channel selection strategies is completed.Finally,based on the simulation results,the performance of different channel selection strategies and the effectiveness of the incentive mechanism is analyzed,which provides theoretical support for the research based on the recommended channel selection strategy in the dynamic spectrum acce ss mechanism.