Channel Estimation Algorithm Based on Compressed Sensing for Underwater Acoustic OFDM Communication System

2015 ◽  
pp. 114-124
Author(s):  
Zhiqiang Zou ◽  
Siyu Lu ◽  
Shu Shen ◽  
Ruchuan Wang ◽  
Xiangyu Lin
Keyword(s):  
Channel Estimation ◽  
Compressed Sensing ◽  
Communication System ◽  
Estimation Algorithm ◽  
Underwater Acoustic

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

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.

A Sparsity Enhanced Channel Estimation Algorithm Based on Compressed Sensing in MIMO-OFDM Systems

2014 ◽  
Vol 35 (3) ◽  
pp. 665-670 ◽  
Author(s):  
Zhi-bin Xie ◽  
Tong-si Xue ◽  
Yu-bo Tian ◽  
Wei-chen Zou ◽  
Qing-hua Liu ◽  
...  
Keyword(s):  
Channel Estimation ◽  
Compressed Sensing ◽  
Estimation Algorithm ◽  
Ofdm Systems ◽  
Mimo Ofdm

Frequency Offset Estimation Algorithm of OFDMA Wireless Communication System Based on Compressed Sensing

2015 ◽  
Vol 7 (3) ◽  
pp. 55-62
Author(s):  
Ma Qinggong ◽  
Yang Bo
Keyword(s):  
Wireless Communication ◽  
Compressed Sensing ◽  
Communication System ◽  
Estimation Algorithm ◽  
Frequency Offset ◽  
Frequency Offset Estimation ◽  
Computation Complexity ◽  
Algorithmic Approach ◽  
Wireless Communication System ◽  
Overall Performance

The frequency offset problem of OFDMA wireless communication system has been an important obstructive factor for the rapid promotion of this technology. The frequency offset estimation algorithm of OFDMA wireless communication system based on compressed sensing reconstructs the optimized mathematical model of frequency offset. Under the premise of keeping its estimated performance, from the reduction of its computation complexity and the enhancement of real-time performance of the system, it provides an optimized algorithmic approach and thus improves the practicability of algorithm. The compressed sensing algorithm has realized the fast and accurate extraction of the frequency offset parameters, so the overall performance of the system can reach the optimal state.

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