Estimation and Equalization of Time-varying Underwater Acoustic Channel Based on Superimposed Training and Low-complexity Turbo Equalization in Frequency Domain
Publication Name
Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology
Abstract
To solve the problems of time-varying underwater acoustic channel estimation and equalization, an estimation and equalization algorithm of time-varying underwater acoustic channel based on Superimposed Training (ST) and Low-complexity Turbo Equalization (LTE) in frequency domain (ST-LTE) is proposed. Based on the ST scheme, the training sequence and symbols are linearly superimposed to make the channel information of the training sequence and symbols consistent; Based on the least square algorithm, channel estimation is performed. Based on the interference elimination technique of training sequence in frequency domain, the interference of training sequence on symbols is eliminated in frequency domain; Based on the Linear Minimum Mean Square Error (LMMSE) equalization algorithm in frequency domain, the low-complexity channel equalization (symbol estimation) is realized by the calculation of prior, posterior, extrinsic mean and variance; Based on the Turbo equalization algorithm, soft reconstruction of superimposed training and update of channel estimation are conducted, the information exchange between equalizer and decoder is also carried out and the performance of channel equalization is extremely improved by using coding redundancy information. Simulation, static communication experiment in a pool (communication frequency is 12 kHz, bandwidth 6 kHz, the sampling frequency 96 kHz, the transmission rate of symbols 4.8 ksym/s and the power ratio of the training sequence on symbols 0.25:1) and moving communication experiment in Jiaozhou Bay (communication frequency is 12 kHz, bandwidth 6 kHz, the sampling frequency 96 kHz, the transmission rate of symbols 3 ksym/s and the power ratio of the training sequence on symbols 0.25:1) are carried out and simulation and experimental results verify the effectiveness of the proposed algorithm.
Open Access Status
This publication is not available as open access
Volume
43
Issue
3
First Page
850
Last Page
856
Funding Number
ZR2020MF001
Funding Sponsor
National Natural Science Foundation of China