Recursive Least Squares Fractionally-spaced Blind Equalization Algorithm for Underwater Acoustic Communication

2013 ◽  
Vol 10 (18) ◽  
pp. 6077-6084 ◽  
Author(s):  
Ying Xiao
Keyword(s):  
Least Squares ◽  
Acoustic Communication ◽  
Blind Equalization ◽  
Recursive Least Squares ◽  
Underwater Acoustic Communication ◽  
Underwater Acoustic ◽  
Equalization Algorithm

A Novel CMA+DD_LMS Blind Equalization Algorithm for Underwater Acoustic Communication

2020 ◽  
Vol 63 (6) ◽  
pp. 974-981
Author(s):  
Jianqiu Sun ◽  
Xingguang Li ◽  
Kang Chen ◽  
Wei Cui ◽  
Ming Chu
Keyword(s):  
Acoustic Communication ◽  
Communication System ◽  
Blind Equalization ◽  
Underwater Acoustic Communication ◽  
Noise Performance ◽  
Step Size ◽  
Underwater Acoustic ◽  
Size Function ◽  
Equalization Algorithm ◽  
Adjustment Factors

Abstract The performance of underwater acoustic communication system is affected seriously by inter-symbol interference caused by multipath effects. Therefore, a novel blind equalization algorithm based on constant modulus algorithm (CMA) and decision-directed least mean square (DD_LMS) is adopted to improve the equalization ability of the system. Firstly, the LMS algorithm is improved by introducing inverse hyperbolic sine function and three adjustment factors to control step-size and the appropriate parameter values are set through the simulation of three adjustment factors. Secondly, the error values of the step-size function are replaced with error expectations to improve the anti-noise performance. Finally, the improved step-size function is introduced into the CMA and DD_LMS algorithm and the difference of the iteration error of adjacent k times is used as the switching condition of the dual mode algorithm. The results show that the algorithm has good equalization and anti-noise performance at both high and low signal-to-noise ratio (SNR), especially at low SNR, its steady-state error is ~10 dB lower than the traditional CMA and its convergence speed is ~15% higher than the traditional CMA. This algorithm can be used to effectively improve the communication efficiency of the communication system of underwater robots, which has good application value.

scholarly journals A low-complexity orthogonal time frequency space modulation method for underwater acoustic communication

2021 ◽  
Vol 39 (5) ◽  
pp. 954-961
Author(s):  
Yang ZHANG ◽  
Qunfei ZHANG ◽  
Yingjie WANG ◽  
Chengbing HE ◽  
Wentao SHI
Keyword(s):  
Acoustic Communication ◽  
Low Complexity ◽  
Modulation Method ◽  
Underwater Acoustic Communication ◽  
Underwater Acoustic ◽  
Frequency Space ◽  
Time Frequency ◽  
Symbol Detection ◽  
Equalization Algorithm ◽  
Infinite Norm

Compared with the orthogonal frequency division multiplexing (OFDM) modulation, the orthogonal time frequency space(OTFS) modulation has a lower peak-to-average power ratio. It can effectively resist the time selective fading caused by the Doppler effect and has significant performance advantages over doubly dispersive channels. However, the conventional OTFS linear minimum mean square error (LMMSE) method has a high complexity and is not easy to process in real time. In order to solve this problem, we propose a low-complexity equalization algorithm with infinite norm constraints based on the optimal coordinate reduction. The equalization algorithm not only obtains the optimal solution through a certain number of iterations and avoids direct matrix inversion but also equalizes infinite norm constraints to improve the symbol detection performance gains. At the same time, the OTFS delay-Doppler channel matrix we utilize is sparse and the two-norm squares of each column vector equally reduces the complexity of optimal coordinate descent. Finally, the simulation in the underwater acoustic communication scenario we designed verify the effectiveness of the proposed equalization algorithm. The simulation results show that the performance of the proposed equalization algorithm is close to that of the LMMSE method, while its low complexity is ensured.

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