Research On The Band Interference Suppression Method Of OFDM Signal Based On Sparse Representation

With the rapid development of wireless communication technologies,the number of wireless communication devices and systems is increasing at this stage.In the case of limited space and tight spectrum resources,serious mutual interference will occur between communication systems in the same frequency band,and the orthogonality between sub-carriers is destroyed,resulting in a large number of in-bands interference in the orthogonal frequency division multiplexing(OFDM)signal,Which prevents the communication system from working properly.In this paper,the problem of in-band interference suppression for OFDM signals is studied.Based on the sparse representation theory and morphological component analysis(MCA)method,the morphological component differences of each component are used to perform sparse representation to achieve interference separation.The specific content of this article is as follows:(1)The basic principle and implementation method of OFDM system are expounded.The simulation analyzes the time domain waveform and spectrum of OFDM signals.The effects of in-band interference on the performance of OFDM systems under different interference powers are discussed from three aspects:spectrum,bit error rate and constellation.(2)The mathematical model of sparse representation and the solution,method of sparse representation model are introduced.The MCA method and three over-complete atom dictionary learning algorithms are introduced.The time of reconstructing signals by three different tracking algorithms is compared and analyzed,and the relationship between reconstruction rate and iteration number at different sparsity levels is also analyzed.(3)Aiming at the suppression of in-band interference of OFDM signals in complex electromagnetic environment,an in-band interference suppression method based on MCA and sparse representation is proposed.The method first analyzes the difference between the in-band interference component and the morphological component of the OFDM signal component,and then uses the dictionary learning algorithm to train the dictionary corresponding to the in-band interference by using the characteristics of each component only sparsely expressed under the corresponding dictionary.Finally,the matching tracking algorithm is used.The interference component is reconstructed and the interference is suppressed at the receiving end.Aiming at the problem that K-value singular value decomposition(K-SVD)algorithm and online dictionary learning(ODL)algorithm dictionary training is limited and the amount of computation is large,the in-band interference suppression of OFDM signal using double sparsity K-SVD algorithm is proposed.The simulation results show that the proposed method can obtain lower error rate than the traditional methods for the three types of in-band interference suppression in the same-band OFDM system,while retaining useful signal information.And the double sparsity K-SVD algorithm can reduce the computational complexity and reduce the computational complexity when the interference reconstruction accuracy is constant.