Research On Nonlinear Dynamic Cognitive Channel Estimation Technology Based On Modern System Approach Method

Spectrum as an important strategic resource of the country, using a fixed way assigned to different fields. However, this approach limits the efficiency of the using of the spectrum with the development of communication. On this issue, the cognitive radio system proposed good solutions. Channel estimation is a key technology to ensure the performance of cognitive radio channel, which plays a very important role in the normal work of cognitive radio system.In this paper, the Jakes simulation model was used to obtain channel fading data and the OFDM system was used as multi-carrier modulation system. The Kalman, EKF and UKF algorithm was used to estimate the system and channel parameters.In this paper, the principles of LS and MMSE algorithm were analyzed, and the effects of channel estimation were compared based on different conditions. The simplified design methods and the channel estimation effect of MMSE algorithm were analyzed for the matrix calculation complexity of MMSE algorithm.In this paper, channel estimation based on Kalman algorithm was realized by abstracting the system and channel model into linear state space equations. The simulation results showed that the Kalman algorithm could track the filtering effect on the time-varying channel accurately. In order to solve the problems of frequency deviation of OFDM system, improved Kalman algorithms were used to estimate the carrier frequency offset of the system. The channel parameter estimation based on UKF and EKF was realized by abstracting the system and channel model into non-linear state space equations. In this paper,channel estimation method based on Kalman algorithm and improved Kalman algorithm was proposed, and the cyclic prefix method was compared. The simulation results showed that the method proposed in this paper had obvious advantages over the BER of cyclic prefix method when the normalized frequency deviation reached 0.3. The UKF algorithm had a performance advantage at the same BER over the EKF algorithm.The research work of this paper belongs to the project of the National Natural Science Foundation of China. During the research period, my research result was included in the international academic conference.