Underwater Acoustic Covert Communication Based on Compressed Sensing

Abstract Compressed sensing technology is currently a relatively mature channel estimation technology, and the sparsity of the underwater acoustic channel provides a basis for the application of compressed sensing technology to the underwater acoustic channel. Channel estimation is one of the most commonly used signal reconstruction methods. The signal is reconstructed based on compressed sensing technology to improve the reliability of signal transmission. The key to compressed sensing technology is the SL0 algorithm. Based on the SL0 algorithm, a new objective function is proposed to better approximate the L0 norm. In a very short time, the original signal can be reconstructed accurately and the signal transmission is improved. Finally a simulation experiment is used to compare the proposed objective function with the previously proposed objective function, which proves that the performance of the proposed objective function is better.

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Compressed Sensing: Underwater Acoustic Channel Estimation with Doppler Shifts

2012 8th International Conference on Wireless Communications, Networking and Mobile Computing ◽

10.1109/wicom.2012.6478459 ◽

2012 ◽

Cited By ~ 2

Author(s):

Huanan Yu ◽

Junyao Guo

Keyword(s):

Channel Estimation ◽

Compressed Sensing ◽

Underwater Acoustic Channel ◽

Underwater Acoustic ◽

Acoustic Channel ◽

Doppler Shifts

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Virtual Time-Inverse OFDM Underwater Acoustic Channel Estimation Algorithm Based on Compressed Sensing

Journal of Sensors ◽

10.1155/2020/5910585 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Yun Li ◽

Xihua Chen ◽

Sanlin Sun ◽

Zhicheng Tan ◽

Xing Yao

Keyword(s):

Channel Estimation ◽

Compressed Sensing ◽

Doppler Shift ◽

Estimation Algorithm ◽

Underwater Acoustic Channel ◽

Underwater Acoustic ◽

Focusing Effect ◽

Acoustic Channel ◽

Channel Information ◽

Virtual Time

The severe multipath delay of the underwater acoustic channel, the Doppler shift, the severe time-varying characteristics, and sparsity make it difficult to obtain the channel state information in the channel estimation of the virtual time-reverse mirror OFDM, which makes the virtual time mirror subcarrier orthogonality easy to suffer damage; the focusing effect is not obvious. Therefore, this paper proposes a virtual time-inverse OFDM underwater acoustic channel estimation algorithm based on compressed sensing. The algorithm extracts the detection signal, constructs a sparse signal model of the delay-Doppler shift, and then performs preestimation of the underwater acoustic channel based on the compressed sensing theory. Then, by predicting the timing of the underwater acoustic channel and convolving with the received signal, the algorithm improves the focusing effect better. Experimental simulations show that compared with LS and OMP algorithms, the algorithm can accurately recover channel information from a small number of observations, reduce the bit error rate by 10%, and improve the accuracy of channel estimation and the time-inverse OFDM performance of virtual time.

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