Variational Bayesian inference-based joint estimation method for underwater acoustic OFDM under impulsive interference  

作　　者：GE Wei JIAO Huakun TONG Wentao SHENG Xueli HAN Xiao 

机构地区：[1]National Key Laboratory of Underwater Acoustic Technology,Harbin Engineering University,Harbin 150001 [2]Key Laboratory for Polar Acoustics and Application of Ministry of Education(Harbin Engineering University),Ministry of Education,Harbin 150001 [3]College of Underwater Acoustic Engineering,Harbin Engineering University,Harbin 150001 [4]State Key Laboratory of Acoustic,Chinese Academy of Science,Beijing 100190

出　　处：《Chinese Journal of Acoustics》2024年第4期487-505,共19页声学学报（英文版）

基　　金：supported by the Excellent Young Scholars Fund of Heilongjiang Province(YQ2022F001);the National Natural Science Foundation of China(62127801,62301181,U20A20329).

摘　　要：To address the severe performance degradation of underwater acoustic orthogonal frequency division multiplexing(OFDM)communication in the presence of impulsive interference,a channel estimation method based on variational Bayesian inference is proposed.This method exploits the sparse characteristics of the underwater acoustic channel and impulsive interference.By utilizing mean-field variational Bayesian inference,this approach decomposes the posterior probability distributions of the channel vector and impulsive interference vector into simple probability distributions for fitting respectively.Iterative estimation is performed based on pilot subcarriers until convergence is achieved,resulting in the maximum a posteriori estimation of the channel and impulsive interference.The proposed method alleviates the problem that one cannot separate the sparsity of channel vector and interference vector in the joint estimation method.Meanwhile,it significantly reduces the computational complexity.Based on this,a joint estimation method of interference,channel,and symbols based on variational Bayesian inference is further proposed,where the unknown symbols are integrated into the variational Bayesian inference framework for iterative estimation with interference and channel,leading to more accurate symbol estimates.Simulation and experimental results demonstrate the effectiveness of the proposed algorithms.Compared to the existing methods,the proposed approach achieves lower error rates and complexity.

关 键 词：method. ESTIMATION IMPULSIVE 

分 类 号：TN929.5[电子电信—通信与信息系统]