Channel Estimation And Narrow Band Inference Detection In OFDM System Based Compressive Sensing

Orthogonal frequency division multiplexing technology has feature of higher bandwidth efficiency and strong resistance to frequency selective fading and so on. Since it is widely used in the field of mobile communication and becomes the core technology of fourth generation communication system. As we all know, according to the Nyquist sampling theorem, digital signal processing in OFDM requires a high sampling rate, however, the current front-end analog to digital converter (ADC) is more difficult to meet their requirements. Therefore, we urgently need to find a new method for solving the digital signal processing problem of OFDM systems.In recent years, due to the compressed sensing theory provides an effective solution for the problem, this theory can simultaneously achieve signal sampling and compression, and then through specific reconstruction algorithm accurately recover the original signal, the method can greatly reduce the sampling rate and the system hardware cost in the communication system.First, in order to improve the performance of OFDM communication system, in-depth analysis of the OFDM communication system channel characteristics and the OFDM system channel estimation technology features, this paper adds the window function into the channel,effectively eliminates the impulse response leak noise generated and ensures that the sparsity of the channel. Further constructing the observation matrix and then the adaptive matching pursuit algorithm is used to recover the channel. The proposed algorithm can adjust the length of a reasonable number of atoms in the candidate set by adaptive step in the condition of unknow the sparsity, and get more accurate estimate of the impact of the response of the channel. Simulation results show that compared with the current channel estimation algorithm,the proposed algorithm can further improve the performance of channel estimation and have a better practical application value.Secondly, in order to further improve the transmission performance of the OFDM communication system. Aiming at the OFDM system detects the presence of narrowband interference problems, in-depth study of the reconstruction algorithm in the theory of compressed sensing, using the adaptive compressed sensing theory of adaptive matching pursuit algorithm to solve narrowband interference detection of the communication system problem, the method can automatically adjust the number of atoms in the candidate set by selecting the appropriate compensation below the Nyquist sampling rate and realize rapidly the single or multiple narrow-band interference signals detecting. Simulation results show that,compared with the existing interference detection algorithms, this algorithm can effectively achieve narrowband interference detection faster and efficiently and improve the performance of OFDM communication system.