| Orthogonal Frequency Division Multiplexing(OFDM)technology has been widely studied for its high frequency band utilization and its effectiveness against frequency selective fading in high-speed underwater acoustic communications.However,the marine environment is complex and volatile,the high-intensity impulsive interference caused by biological movement and artificial operations seriously affects the performance of OFDM underwater acoustic communication.Thus,the main objective of this paper is to study how to suppress impulsive interference in OFDM systems and achieve robust communication in impulsive interference environments.Firstly,this paper conducts modeling and analysis of channel characteristics and impulsive interference characteristics.Based on this analysis,the key technologies of OFDM receivers,including channel estimation and channel equalization,are investigated.Taking channel estimation as an example,the performance differences between OFDM systems with and without impulsive interference are simulated and compared.Furthermore,in order to enhance the performance of OFDM communication systems under impulsive interference,this paper investigates interference suppression methods based on Improved Sparse Bayesian Learning(ISBL).The research is primarily focused on three aspects: Firstly,an interference suppression method based on pilot-based ISBL is investigated.In this method,the presence of impulsive interference in the OFDM receiver model is considered,and a unified vector combining the interference vector and the channel vector is used for joint estimation.The time-domain impulsive interference is extracted and removed from the received signal,followed by equalization and decoding.Compared to conventional Least Squares(LS)and Sparse Bayesian Learning(SBL)channel estimation methods,impulsive interference suppression can be effectively achieved.Secondly,a joint estimation method for interference and channel is studied by combining ISBL and bi-directional Kalman filtering.The time-varying nature of the channel is taken into account,and the correlation between adjacent OFDM symbols is utilized to improve channel estimation accuracy.The estimation precision is enhanced by exploiting the temporal channel correlations.Thirdly,a joint estimation method for interference,channel and symbol based on ISBL is investigated.This method makes use of symbol information on all subcarriers and incorporates the unknown symbols on data subcarriers into the ISBL framework for iterative estimation.The accuracy of symbol estimation is improved,and good robustness in impulsive interference environments is demonstrated.Lastly,the limitations of the ISBL interference and channel joint estimation method,which fails to consider the sparsity of both the interference vector and the channel vector,resulting in performance degradation and high computational complexity,are addressed in this paper.A novel approach based on Variational Bayesian Inference(VBI)is proposed for OFDM channel estimation and interference suppression.By leveraging the mean field theory,the interference vector and the channel vector are separated and estimated,reducing the computational complexity while improving the channel estimation accuracy.Furthermore,a joint estimation method for interference,channel,and symbol based on VBI is introduced.This method utilizes VBI for iterative estimation of unknown symbols on the data subcarriers,further enhancing estimation accuracy and reducing the system’s bit error rate.Both numerical analysis and experimental data processing results demonstrate that the VBI-based approach outperforms the ISBL-based method in terms of lower channel estimation mean squared error and system bit error rate.Thus,it ensures the robustness of OFDM communication in impulsive interference environments. |
