鄢社锋,
1.中国科学院声学研究所 北京 100190
2.中国科学院大学 北京 100049
基金项目:国家自然科学基金(61725106)
详细信息
作者简介:赵世铎：男，1994年生，博士生，研究方向为OFDM水声通信技术
鄢社锋：男，1978年生，教授，博士生导师，研究方向为阵列信号处理、水声通信等
通讯作者:鄢社锋 sfyan@ieee.org
中图分类号:TN929.3计量
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被引次数:0
出版历程
收稿日期:2020-07-15
修回日期:2020-12-04
网络出版日期:2020-12-30
刊出日期:2021-03-22
Low-complexity Iterative Sparse Channel Estimation for Underwater Acoustic OFDM Systems Based on Generalized Path Identification Algorithm
Shiduo ZHAO,Shefeng YAN,
1. Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
2. University of Chinese Academy of Sciences, Beijing 100049, China
Funds:The National Natural Science Foundation of China (61725106)
摘要
摘要:移动OFDM水声通信系统中，基于压缩感知的稀疏信道估计方法计算量较大，不适用于实时通信。针对这一问题，该文基于一致多普勒信道模型提出一种扩展路径识别(GPI)算法。该方法首先使用信道多普勒扩展矩阵构造等效发射序列，将多普勒信道转化为等效线性时不变信道。然后使用GPI算法估计信道多普勒及各路径的时延及幅度参数，实现低复杂度稀疏信道估计。此外，该文将GPI算法扩展到Turbo接收机中，通过利用信道译码器反馈的数据符号先验信息迭代提高信道估计精度。仿真结果表明，所提方法的性能优于传统的路径识别算法，且与OMP算法接近，而其计算量远低于后者。
关键词:OFDM水声通信/
稀疏信道估计/
扩展路径识别算法/
OMP/
Turbo接收机
Abstract:In mobile OFDM underwater acoustic communication systems, the compressed sensing-based sparse channel estimation methods suffer from high computational complexity, which is not suitable for real-time communication. To solve this problem, this paper proposes a Generalized Path Identification (GPI) algorithm for estimating uniform Doppler distorted channel. This scheme first constructs equivalent transmitted symbols using Doppler spread matrices, and thus the channel is converted into an equivalent linear time-invariant one. Then the GPI algorithm is utilized to estimate the channel parameters. Furthermore, the GPI algorithm is extended to Turbo receivers to iteratively improve the channel estimation accuracy. Simulation results show that the performance of the proposed method is better than that of the conventional path identification algorithm, and is close to the Orthogonal Matching Pursuit (OMP) algorithm. Its computational complexity, however, is much lower than OMP algorithm.
Key words:Underwater acoustic OFDM communications/
Sparse channel estimation/
Generalized Path Identification (GPI) algorithm/
Orthogonal Matching Pursuit (OMP)/
Turbo receiver
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