基于数据样本方差的正交频分复用水声通信多普勒频移估计方法

周成阳; 王巍; 洪丹阳; 张春华

doi:10.11999/JEIT210348

基于数据样本方差的正交频分复用水声通信多普勒频移估计方法

doi: 10.11999/JEIT210348

周成阳^{1, 2, 3},
王巍^{1, 3},
洪丹阳^{1, 2, 3},
张春华^{1, 3, ,}

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
3.
中国科学院先进水下信息技术重点实验室北京 100190

基金项目: 中国科学院声学研究所所长基金(Y754191211)

详细信息

作者简介:
周成阳：男，1995年生，博士生，研究方向为水声通信

王巍：男，1983年生，副研究员，研究方向为水声通信、水下无线传感器网络

洪丹阳：男，1994年生，博士生，研究方向为水声通信

张春华：男，1962年生，研究员，研究方向为阵列信号处理、水下无线传感器网络和合成孔径声呐等

通讯作者:
张春华　zch@mail.ioa.ac.cn

中图分类号: TN929.3
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- 被引次数: 0
出版历程
- 收稿日期: 2021-04-23
- 修回日期: 2021-07-16
- 网络出版日期: 2021-07-26
- 刊出日期: 2022-06-21

Doppler Frequency Shift Estimation Method for Orthogonal Frequency Division Multiplexing Underwater Acoustic Communication Based on Data Sample Variance

ZHOU Chengyang^{1, 2, 3},
WANG Wei^{1, 3},
HONG Danyang^{1, 2, 3},
ZHANG Chunhua^{1, 3
, ,}

1.
Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
2.
University of Chinese Academy of Sciences, Beijing 100049, China
3.
Key Laboratory of Science and Technology on Advanced Underwater Information of Chinese Academy of Sciences, Beijing 100190, China

Funds: The Director’s Fundation of Institute of Acoustics, Chinese Academy of Sciences (Y754191211)

摘要

摘要: 针对正交频分复用(OFDM)水声移动通信易受时变多普勒频移影响的缺点，该文提出一种基于数据样本方差的多普勒频移估计方法。利用前序符号的信道估计值恢复当前符号的有效数据序列及其频域分集副本，计算分集副本与数据序列的比值并搜索该比值序列在不同多普勒补偿因子下的方差，选取方差最小时对应的补偿因子作为多普勒频移估计值，利用稀疏贝叶斯学习和判决反馈信道估计算法获得修正后的信道频域响应并传递给后序符号，实现对多普勒频移的实时跟踪。数值仿真验证了该方法的可行性和优越性，海上试验证明，该方法实现了基于无人水下航行器的OFDM水声移动通信，能够对时变多普勒频移进行有效估计。
- 水声通信 /
- 正交频分复用 /
- 多普勒频移估计 /
- 频域分集
Abstract: To overcome disadvantages of Orthogonal Frequency Division Multiplexing(OFDM) underwater acoustic mobile communication, a data variance-based Doppler frequency shift estimation method is proposed to estimate the time-varying Doppler shifts. The estimated channel response of previous OFDM symbol is utilized to recover the valid data sequence and its frequency-domain diversity. The variance of the ratio of data sequence and diversity copy are calculated under different Doppler compensation factors. Then the correct Doppler frequency shift factor is achieved by seeking the minimum of the variance. Sparse Bayesian learning and decision feedback channel estimation algorithm are used for calculating the revised channel frequency-domain response. The channel response is propagated to the follow-up symbol to track the time-varying Doppler shifts. The feasibility and superiority of the proposed method are verified by simulation. The sea trail demonstrates that the proposed algorithm can effectively estimate the Doppler shifts in underwater acoustic OFDM mobile communication for Unmanned Underwater Vehicle.
- Underwater acoustic communication /
- Orthogonal Frequency Division Multiplexing(OFDM) /
- Doppler frequency shift estimation /
- Frequency domain diversity

HTML全文

图 1 OFDM水声通信数据样本方多普勒估计算法系统框图

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图 2 通信信号的帧结构示意图

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图 3 水声信道冲激响应

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图 4 数据样本方差与多普勒频移的关系

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图 5 不同信噪比下多普勒频移估计误差

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图 6 不同信噪比下原始误码率对比

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图 7 通信时段信道冲激响应

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图 8 低航速试验不同多普勒频移估计算法对比

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图 9 高航速试验通信时段信道冲激响应

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图 10 高航速试验不同多普勒频移估计算法对比

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表 1 不同多普勒频移估计算法所需计算量

多普勒频移估计算法	复数乘法	复数加法
单频测频	2.46×10⁵	4.92×10⁵
空子载波	4.20×10⁷	4.20×10⁷
信道稀疏度检测	1.05×10⁷	2.10×10⁷
本文算法	4.92×10⁶	9.84×10⁶

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表 2 OFDM系统仿真参数

参数	数值	参数	数值
采样率(kHz)	192	OFDM符号周期(ms)	170.7
通信频段(B/kHz)	4～8	循环前缀长度(ms)	43
有效子载波数	681	数据映射方式	QPSK

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表 3 低航速下不同多普勒频移估计方法的误码率统计结果

多普勒频移估计算法	原始误码率	解码后误码率
本文算法	0.0200	7.960×10^–5
空子载波算法	0.0390	4.117×10^–4
单频测频	0.0704	4.401×10^–3
信道稀疏度检测	0.0305	9.157×10^–4

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表 4 高航速下不同多普勒频移估计方法的误码率统计结果

多普勒频移估计算法	原始误码率	解码后误码率
本文算法	0.0435	6.340×10^–4
空子载波算法	0.0862	4.795×10^–3
单频测频	0.1174	7.351×10^–3
信道稀疏度检测	0.0639	2.180×10^–3

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