Research On OFDM Signal Interference Suppression Method Based On Sparse Representation Theory

The development of wireless communication technology has made orthogonal frequency division multiplexing (OFDM) technology more and more widely used.Due to the complexity of the electromagnetic environment,the transmitted OFDM signal is easily cascaded into other communication signals.When the characteristics of the transmission signal and the channel are not clear,traditional interference suppression methods are often unable to effectively separate or suppress the interference components in the OFDM signal band to obtain the required useful signals.Based on the theory of sparse representation,this thesis studied the problem of in band interference suppression of OFDM signal.The main research contents are as follows:1.Introduced the basic principles of OFDM and built an OFDM system model under in-band interference.The performance of the OFDM system;model under single-carrier communication interference and the OFDM system model under narrow-band interference(NBI) are simulated and analyzed from the three aspects of time-domain waveform diagram,spectrum diagram and constellation diagram.2.The sparse representation theory of signals is expounded from two aspects:sparse representation based on over-complete dictionary and sparse representation based on compressive sensing (CS).This thesis compared and introduced three sparse decomposition algorithms,basis pursuit (BP),matching pursuit (MP),orthogonal matching pursuit (OMP),and the learning dictionary algorithm method of optimal directions (MOD) and K-singular value decomposition (K-SVD),and the training time and reconstruction error of the two learning dictionary algorithms are compared and analyzed.3.Aiming at the problem of interference suppression of single carrier communication in OFDM signal band,a method of interference suppression based on the learning dictionary and symbol synchronization information is proposed.Firstly,according to the difference of the morphological components of OFDM signal and interference signal,the K-SVD algorithm is used to construct the learning dictionary of OFDM signal and interference signal respectively.Secondly,the input sample signal is divided into symbol period,then decomposed and reconstructed,and the reconstructed signals are cascaded to get the complete reconstruction signal.Finally,use the cancellation method to complete the suppression of the interference signal.The simulation results show that the proposed method improves the decomposition accuracy and reconstruction probability of the signal,and has better interference suppression effect than the traditional nulling method.4.Aiming at the problem of NBI suppression in OFDM signal band,an interference suppression method based on fast iterative CS is proposed.Firstly,the NBI is sparse represented by Fourier transform basis,and then the dimension of sparse signal is reduced by Gaussian random observation matrix.Secondly,the fast iterative algorithm is combined with the reconstruction algorithm to realize the high probability reconstruction of the interference signal.Finally,the cancellation method is used to suppress the interference signal.The simulation results show that the proposed method has better interference suppression effect than the traditional CS method and the nulling method,and with the increase of signal reconstruction iterations,the suppression effect is getting better and better.Ideally,when the iterations are enough,the system performance without interference can be achieved.The research results show that the proposed single-carrier communication interference suppression method based on learning dictionary and symbol synchronization information and the NBI suppression method based on fast iterative CS have good interference suppression effects,which can effectively reduce the bit error rate of the system,and have a certain practicality.