Research On Multi-Objective Resource Optimization Mechanism In Cognitive Radio Networks

Cognitive radio technology brings revolutionary challenge to the traditional static spectrum allocation strategy, and gradually becomes the focus of research in the field of wireless communications. In actual wireless network, although cognitive radio can alleviate the problem of low spectrum utilization which is caused by the traditional spectrum allocation method, the wireless network based on cognitive radio technology has also become very complex. In the complex wireless network, in order to achieve optimal communication quality, multiple communication resources are needed to meet the optimal state to achieve the best communication efficiency, which can adapt to the rapid development of wireless communication technology. So how to realize the joint optimization of multiple communication resources and meet the optimal network performance is a focus which needs to be solved urgently in cognitive radio network. Therefore, the multi-objective resource optimization mechanism in cognitive radio network has been researched in this thesis. The main contents include the following two aspects:1. The first part focuses on the problem of how to realize channel allocation efficiently and fairly in cognitive radio network. In order to solve the difficult multi-objective channel allocation issue about maximizing network efficiency and users' fairness to access network, a new discrete multi-objective optimization mechanism based on Hooke Jeeves and quantum particle swarm optimization algorithm is proposed. This thesis converts the physical model of channel allocation in cognitive radio network into mathematical model to obtain an optimal channel allocation scheme. The simulation results show this optimization mechanism can better approximate the optimal solution and converge fast. Under the constraints of multiple optimization objectives, the mechanism can obtain a channel allocation scheme which is more efficient and fair.2. The second part focuses on the problem the multi-objective optimization problem of admission control and power control in cognitive radio network. To solve the optimization problem of admission control and power control of secondary users in cognitive radio networks, a new scheme is proposed based on the discrete particle swarm optimization and simplex method to realize the joint optimization of admission control and power control. Under the constraint of interference temperature and the quality of service of secondary users, the admission control is modeled as 0-1 combinatorial optimization problem and the power control is transformed into a linear constraint problem. In order to reduce the complexity of the scheme, a feasibility verification method of combined optimization of admission control is proposed. The simulation results and analysis show that the proposed scheme not only can effectively increase the number of secondary users admitted and reduce power consumption, also can obtain convergence and improve the performance of network optimization.