基于深度学习的OFDM半相干水声通信方法
OFDM semi-coherent underwater acoustic communication method based on deep learning
寇旭 1房小芳 2朱敏 3武岩波3
作者信息
- 1. 中国科学院声学研究所海洋声学技术实验室,北京 100190;中国科学院大学,北京 100049
- 2. 中国科学院声学研究所海洋声学技术实验室,北京 100190;中国科学院声学研究所北京市海洋声学装备工程技术研究中心,北京 100190
- 3. 中国科学院声学研究所海洋声学技术实验室,北京 100190;中国科学院声学研究所北京市海洋声学装备工程技术研究中心,北京 100190;中国科学院声学研究所声场声信息国家重点实验室,北京 100190
- 折叠
摘要
针对正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)水声通信中常用的相干和非相干通信分别面临的对多普勒敏感和频谱效率低的问题,提出一种高阶幅度键控调制的半相干通信技术,将OFDM符号时频帧结构中全部频点采用高阶幅度键控调制方式,并利用信号幅度信息完成半相干信道估计.通过两种基于深度学习的算法优化半相干信道估计这一非线性过程,较非相干通信有效提高了频谱效率,较一定信噪比下的相干通信提高了鲁棒性,降低了误比特率和系统复杂度,并利用元学习算法降低深度学习算法对训练数据的依赖.最后,提取海试信道数据,完成OFDM半相干水声通信系统仿真,验证了所提方法在频谱效率和系统误比特率性能方面较非相干和相干通信的优势,当信道长度改变时,基于元学习的算法依然可以获得较好的性能.
Abstract
To solve the problems of Doppler sensitivity and low spectral efficiency of the coherent and non-coherent communication commonly used in orthogonal frequency division multiplexing(OFDM)underwater acoustic communication,a semi-coherent communication technique with M-ary amplitude shift keying is proposed,in which,all the frequencies in the OFDM symbolic time-frequency frame structure are modulated with M-ary amplitude shift keying and the semi-coherent channel estimation is accomplished with the signal amplitude information.By optimizing the nonlinear process of semi-coherent channel estimation with two deep learning algorithms,the spectral efficiency is improved compared to the non-coherent communication and the robustness is improved;meanwhile,the bit error rate and system complexity are reduced compared to the coherent communication at a certain signal to noise ratio.Moreover,the meta-learning-based algorithm is used to reduce the dependence of the deep learning algorithm on the training data.Finally,the simulation of OFDM semi-coherent underwater acoustic communication system is completed by using the actual channel data obtained from sea trial,and the results verify the advantages of the proposed method over non-coherent and coherent communication in terms of spectral efficiency and system bit error rate.And,the meta-learning-based algorithm can still obtain better performance when the channel length changes.
关键词
半相干水声通信/正交频分复用(OFDM)技术/信道估计/深度学习/元学习Key words
semi-coherent underwater acoustic communication/orthogonal frequency division multiplexing(OFDM)/channel estimation/deep learning/meta learning引用本文复制引用
基金项目
国家自然科学基金(61971472)
中国科学院战略性先导科技专项(XDA22030101)
国家重点研发计划(2021YFC2800200)
中国科学院声学研究所自主部署项目(QYTS202003)
出版年
2024
NETL
NSTL
万方数据