In-band Multiple Single-carrier Communication Interference Suppression Method for OFDM Signal Based on Learning Dictionary and Symbol Synchronization Information

Aiming at the difficulty of traditional interference suppression methods for orthogonal frequency division multiplexing (OFDM) signal in-band multiple single-carrier communication interference suppression,an interference suppression method based on learning dictionary and symbol synchronization information was proposed. According to the difference of morphological components between different communication signals,the K-singular value decomposition (K-SVD) algorithm was used to train the OFDM signal and multiple interference signals in turn to obtain the over-complete dictionary that met the characteristics of each signal. To ensure the effective distinction between the signals. When the over-complete dictionary was used to sparsely decompose the interference signal,first used the symbol synchronization information to segment the interference sample signal,and then used the orthogonal matching pursuit (OMP) algorithm for sparse decomposition to improve the decomposition accuracy of interference signals in different symbol periods. Finally,the cancellation method was used at the receiving end to sequentially suppress the reconstructed interference signals. The simulation results show that the proposed method can effectively suppress the interference models composed of 2PSK and MSK,2PSK and 2FSK,and can effectively improve the system performance compared with the traditional frequency domain nulling method.