Research On Resource Management And Traffic Scheduling In Cognitive Radio Networks

As the fast development of wireless communication technology, the number of users increases in a rapid speed. The users’requirements for service quality become higher which leads to serious need for wireless spectrum. However, it’s hard to allocate free spectrum band to new users for the reason that the existing spectrum has been assigned. Moreover, the efficiency is low for the spectrum which has been allocated. As a result, the conflict between the shortage of wireless spectrum resource and low spectrum efficiency has becoming serious. Cognitive radio technology, an important direction for future mobile communication development, has been a promising way to solve the conflict which can make full use of the free spectrum resource without influencing the Authorized business. On the other hand, the spectrum efficiency can also be increased.Generally, cognitive radio senses particular spectrum band and seek free spectrum resource through spectrum sensing technology. To improve the spectrum efficiency, it allocates the spectrum reasonably according to time, frequency, space through dynamic spectrum management. Through sensing technology, the cognitive network with the aim of realizing QoS from end to end and achieving load balance can obtains the information of the network status, dispatch the business flow reasonably and fully optimize the configuration of resources. Currently, quite a lot research institutions and researchers have do much work on related area and they have achieved a lot, however, various problems remains to be solved.In this paper, we aim at optimizing the spectrum management, improving the property of the network flow schedule and increasing the spectrum efficiency for the cognitive radio network. To achieve this, we do research on cooperative spectrum sensing, dynamic spectrum access and flow schedule of cognitive radio resource management. We not only propose the corresponding improved scheme and algorithm, but also demonstrate them through theoretic analysis and simulation. The main work and innovation are presented in the following:1) A new cooperative spectrum sensing scheme in cognitive radio networks based on evolutionary game is proposed. We first analyze the secondary users’ transmission time and throughput, model the cooperative sensing as an evolutionary game, derive the dynamic procedure and optimal strategy for the secondary users, and further develop a distributed learning algorithm. Analysis and simulation show that the proposed scheme guarantees sensing reliability without any performance loss and reduces the communication overhead significantly to achieve high throughput for secondary user in sensing cooperation.2) We propose a dynamic spectrum allocation scheme in cognitive radio networks based on Stackelberg game. In our model, primary user is the game leader and determines the interference price charged to secondary user. Meanwhile, a group of secondary users are the game follower and determines their bandwidth demand in response to primary user’s decision. A distributed algorithm is proposed to find the Nash equilibrium for the bandwidth leasing game, and further propose an incentive-compatible mechanism for primary user and secondary users to achieve the social welfare optimality.3) We propose a traffic scheduling algorithms based on Hopfield neural network for cognitive packet networks. The method first establish multi path routing with QoS guarantee for each source-destination nodes in the network, then based on the real time network status information, combine the Hopfield neural network and flow deviation algorithm for flow allocation among the links to reduce the end-to-end delay, and further propose an traffic scheduling mechanism to balance the flow of links in the network, improve the overall network performance.The research in this thesis has theory and practical value for cognitive radio and cognitive radio networks, and has reference value to other wireless networks.