Fast Time Varying Channel Estimation Based On State Space Method In Cognitive Radio

With the rapid development of mobile communication technology and the constantly emerging of new wireless communication products,people's demand for the high speed and efficiency of data transmission has increasingly more and more fast.The scarcity of spectrum resources is becoming increasingly serious,in this case,the cognitive radio technology came into being.At present,the mobile behavior of the user or the working environment of the wireless communication under the non ideal conditions will lead to time-varying fading of the wireless channel.At this point,the actual performance of the key technologies of cognitive radio networks designed under ideal conditions will be affected,and even can not work In extreme cases properly.Faced with this problem,this paper mainly focuses on the study of related technology research between the fading channel and the cognitive radio system under the condition of dynamic and uncertainty.To solve the problem of channel estimation techniques in NC-OFDM transmission under non ideal conditions.Make full use of the time varying characteristics of the authorized user's state and gain's state transfer of information,in this paper we designed a dynamic state space model of spectrum sensing under time varying fading channels.To solve the problem in the estimation and spectrum sensing method for cognitive radio channel based on static channel caused by the uncertainty of dynamic time-varying fading channels,we describe the time-varying fading channel gain along with time migration,then a joint estimation algorithm based on dynamic state space model is proposed in this paper,which is focus on the joint estimation of the working state and the gain of the time varying channel for the main user.After the implementation of spectrum sensing on the basis of joint estimation,and analysis the impulse response in the time domain or frequency domain of the wireless transmission channel,then the article mainly aimed at the characteristics of the fast time varying channel.A fast time varying channel estimation technique based on the unscented kalman filter algorithm is studied.And the T-S fuzzy system has been used for the optimization of the system.On the basis of this,a strong tracking filtering technique is also introduced to improve the performance of the algorithm and improve the robustness of the whole system.The proposed optimization algorithm maintains the real-time tracking of the channel state changes while improving the accuracy of the channel response estimation,which plays a role in improving the performance of the estimation performance of the fast time-varying channel.By computer simulation,the simulation results show that:the model of each part in the technology and method verifying the validity and feasibility of the model.