Research Of Cognitive Radio Network Key Techniques Under Underlay Model

In recent years, with the explosive growth of wireless communication services, the problems of limited spectrum resource and low utilization rate become more and more prominent. How to improve the efficiency of spectrum utilization has become an important issue in the field of wireless communication. As a new intelligent communication technology, cognitive radio is receiving more and more attention by aiming at allocation method and access method for spectrum resource. It can adaptively adjust the parameters of the system, quickly and effectively fill the spectrum holes or unused spectrum, and solve the problem of low spectrum utilization. In the cognitive radio system, the rational allocation of the spectrum and the emission power control is the key to achieve the spectrum sharing. So the problem of spectrum allocation and power control are naturally concerned by scientific researchers. On the basis of previous studies, this paper tries to use new theory and mathematical tools to obtain new cognitive radio spectrum sharing and power control multi-objective optimization method, and gives the corresponding solutions. The main research work of this paper is as follows:In order to solve the problem of low utilization of spectrum resources, this paper transforms the optimization problem into multi-objective optimization problem. This paper also takes the primary user’s network benefit and the secondary user’s interference as optimization object, establishes the spectrum allocation model based on Underlay mode, and optimizes the allocation of spectrum resources by using the multi-objective optimization algorithm based on intelligent optimization algorithm. In this algorithm, the spectrum allocation method of each secondary user is used as the genes, the spectrum allocation scheme for all secondary users is composed of a distribution scheme as an individual, multiple allocation schemes constitute the distribution scheme set as the population, and find a set of optimal solutions by using multi-objective intelligent optimization algorithm. Simulation experiments show that the proposed algorithm can effectively improve the network efficiency and reduce the interference to the primary users.In order to solve the power control problem in cognitive wireless network, this paper take the minimization of the secondary user power and the maximization of the network benefit as optimization goal and establishes the power control model. Moreover, this paper proposes a multi-objective optimization algorithm based on target weight factor directed particle swarm optimization. In the process of optimization, the feasible solutions are obtained and the global extreme value of each particle in the population is close to its own emphasis, so as to maintain the diversity of solutions. Simulation experiments show that the proposed algorithm can achieve the optimal power control, save energy and improve the performance of the whole network.