Research On Some Key Techniques Of The Cognitive Radio Systems

With the development of wireless communications technology, the spectrum resources are increasingly scarce. In order to solve the problem of insufficient spectrum resources, the cognitive radio technology based on the opportunity spectrum access mechanism plays a more important role. Cognitive radio technology subverts the traditional fixed spectrum allocation fundamentally. It can sense changes of the environment by the sensing node, and change the transmission power, modulation, carrier frequency and other transmission parameters to improve the efficiency of spectrum. Spectrum allocation is a key technology in cognitive radio systems. It can allocate the free spectrum resources and ensure a higher spectrum efficiency. The spectrum sensing technology is used to make sure that the spectrum is not used by the primary user. The cognitive radio system must detect the interference power nearby the primary user's receiver to ensure the interference power from the secondary user is less than a threshold. So the cognitive radio system must know the location information of the primary user.In this dissertation, we research on the spectrum allocation, spectrum sensing and primary user tracking problems in the cognitive radio system. The main contributions of the dissertation are as follows:(1) A new spectrum allocation algorithm for cognitive radio is proposed based on the analysis of the OFDM based cognitive radio system. For this system that the constant rate users and the variable rate users are coexistence with each other, the proposed algorithm is minimizing the transmitted power per bit, allocating the free spectrum in the cognitive radio cell dynamically in a sense of fair maximization. The system object function is simplified by using the min-max criterion and the step by step approach.(2) A cyclo-energy detector is proposed for the spectrum sensing problem based on the cyclostationary signal analysis. It can determine whether there exists primary user by estimating the primary user's received power according to the cyclostationarity of the secondary user. By using this detector, the secondary user need not stop transmitting when sensing the frequency spectrum.(3) By using the features which most of the received signals are correlated, a joint energy and autocorrelation based spectrum sensing algorithm is proposed. The hypothesis testing formula has been derived, and the detection probability of the primary user has been improved. (4) The primary user location problem is a key issue of the cognitive radio system. Locating the primary user's accurate position can provide a better service for the users. The random set based Gaussian mixture probability hypothesis density filter algorithm is a typical multi-target tracking algorithm. It can track multiple targets when the number of the targets is unknown. In this dissertation, a modified Gaussian mixture probability hypothesis density filter is developed for multi-target tracking problem because the traditional Gaussian mixture probability hypothesis density filter can not work well when where the targets will appear is unknown. And the proposed algorithm is applied to track the primary users in the cognitive radio systems. A double side prediction algorithm is adopted to solve this primary user tracking problem. First, the forward prediction algorithm is used to estimate the locations of the existed primary users, and then the backward prediction algorithm is used to search the new primary users. The proposed algorithm can be used when we do not know how many primary users exist, and when and where they will appear. Simulation results show that the proposed algorithm can track the primary users even in a high false detection environment.