基于快速信息收集和虚拟训练序列的低复杂度双向水声信道精准估计

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中文摘要：针对运动水声通信难以低复杂度精准获取时变信道状态信息的问题,提出基于快速信息收集和虚拟训练序列(FIC-VT)的低复杂度双向水声信道精准估计算法.采用叠加训练(ST)方案,将符号序列和训练序列线性叠加,使得训练序列持续传输,提高时变信道跟踪能力.基于置信传播,提出FIC-VT算法,将一块数据分成多个短块,每个短块又分成多个子段,通过快速信息收集算法,将多个子段的信道信息进行融合,从而获得每个短块的低复杂度局部信道估计.利用短块间的信道相关性,对多个短块的信道信息进行双向信息融合,从而获得当前短块的低复杂度全局信道估计.基于Turbo均衡,将估计的符号序列虚拟为训练序列(VT),通过迭代计算实现时变水声信道低复杂度精准估计.本文算法由快速傅里叶变换(FFT)实现,每个抽头计算复杂度仅为对数级.计算机仿真、水池运动通信试验和胶州湾运动通信试验验证了本文算法的有效性.

外文标题：Accurate estimation of low complexity bidirectional underwater acoustic channels based on fast information collection and virtual training sequence

外文摘要：Aiming at the difficulty of accurately obtaining time-varying channel state information in moving underwater acous-tic communication with low complexity,a low complexity bidi-rectional underwater acoustic channel estimation algorithm based on fast information collection and virtual training (FIC-VT) was proposed. A superimposed training (ST) scheme was adopted to linearly superimpose a symbol sequence and training sequence to ensure continuous transmission of the training sequence and improve the time-varying channel track-ing capability. Based on belief propagation,the FIC-VT algo-rithm was proposed,which divided a block of data into multi-ple short blocks,each of which was divided into multiple sub segments,and by a fast information collection algorithm,the channel information of multiple sub segments was fused to ob-tain low complexity local channel estimates for each short block. Turbo equalization was employed to virtualize the esti-mated symbol sequence into a virtual training sequence (VT),and through iterative calculation,the proposed algo-rithm eventually achieves low-complexity and accurate estima-tion of time-varying underwater acoustic channels. The pro-posed algorithm is implemented by using fast Fourier transform (FFT),with computational complexity per tap at a logarith-mic level. The effectiveness of the proposed algorithm is veri-fied through computer simulation,pool motion communication experiments,and Jiaozhou Bay motion communication experi-ments.

外文关键词：

time-varying underwater acoustic channellow complexity bidirectional channel estimationfast information collectionvirtual training sequencesuperimposed trainingfast Fourier transform(FFT)

作者：

陈建军、曲亚东、梁俊燕、孙冬雪、李森

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作者单位：

青岛理工大学信息与控制工程学院,山东青岛 266525

大连海事大学信息科学技术学院,辽宁大连 116026

关键词：

时变水声信道低复杂度双向信道估计快速信息收集虚拟训练序列叠加训练快速傅里叶变换(FFT)

基金：

山东省自然科学基金资助项目国防科技创新特区项目

项目编号：

ZR2021QF113

出版年：

2024

DOI：

10.16411/j.cnki.issn1006-7736.2024.03.002

大连海事大学学报

大连海事大学

大连海事大学学报

CSTPCD北大核心

影响因子：0.469

ISSN：1006-7736

年,卷(期)：2024.50(3)