Research on Variable Step-Size Blind Equalization Algorithm Based on Normalized RBF Neural Network in Underwater Acoustic Communication

Author(s):  
Xiaoling Ning ◽  
Zhong Liu ◽  
Yasong Luo
2020 ◽  
Vol 63 (6) ◽  
pp. 974-981
Author(s):  
Jianqiu Sun ◽  
Xingguang Li ◽  
Kang Chen ◽  
Wei Cui ◽  
Ming Chu

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.


2012 ◽  
Vol 457-458 ◽  
pp. 961-967
Author(s):  
Xiang Zhao ◽  
Jin Yong Sun ◽  
Han Hong Tan

A variable step size Constant Modulus Algorithm (CMA) based on the gamma distribution is implemented as solutions to optimize the problem of blind equalization. The factor of step size in blind equalization algorithm is varied with gamma variable, in terms of the characteristics of which, the algorithm can search for the globe optimal equalizer weight vector. Simulation results indicate that the convergence rate and the steady Mean Square Errors (MSE) performances of the algorithm proposed are much better than conventional CMA and modified CMA blind equalization algorithms.


Author(s):  
Doaa Ashmawy ◽  
Kevin Banovic ◽  
Esam Abdel-Raheem ◽  
Mohamed Youssif ◽  
Hala Mansour ◽  
...  

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