Modified Variable Step Size FLOM-CMA Based on Lorentzian Function under Impulse Noise

Aiming at the problem that the traditional equalization algorithm under impulse noise is difficult to suppress impulse noise and achieve equalization, a new modified variable step size FLOM-CMA algorithm based on Lorentzian function is proposed in this paper. The proposed algorithm has modified the cost function to made full use of the phase information of signal to correct the phase rotation. Also, by adjusting the FLOM of cost function, that impulse noise is restrained effectively. Furthermore, the Lorentzian function is use to update the step size to make sure it is is appropriate for each equalization point. Simulation experiments show that, compared with FLOM-CMA and VS-FLOM-CMA, the proposed algorithm that the proposed algorithm achieves higher convergence accuracy with similar convergence speed. And under different impulse noise conditions, the robustness of the algorithm is better.

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Network Intrusion Feature Map Node Equalization Algorithm Based on Modified Variable Step-Size Constant Modulus

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001419550152 ◽

2019 ◽

Vol 33 (14) ◽

pp. 1955015 ◽

Cited By ~ 1

Author(s):

Jiazhong Lu ◽

Xiaolei Liu ◽

Teng Hu ◽

Jianwei Zhang ◽

Xiaosong Zhang

Keyword(s):

Channel Model ◽

Channel Equalization ◽

Variable Step Size ◽

Transmission Channel ◽

Constant Modulus ◽

Step Size ◽

Feature Map ◽

Network Intrusion ◽

Equalization Algorithm ◽

Variable Step

When the network is subject to intrusion and attack, the node output channel equalization will be affected, resulting in bit error and distortion in the output of network transmission symbols. In order to improve the anti-attack ability and equalization of network node, a network intrusion feature map node equalization algorithm based on modified variable step-size constant modulus blind equalization algorithm (MISO-VSS-MCMA) is proposed. In this algorithm, the node transmission channel model after network intrusion is constructed, and sequential processing is performed to intruded nodes with the variable structure feedback link control method. With diversity spread spectrum technology, the channel loss after network intrusion is compensated and the network intrusion map feature is extracted. According to the extracted feature amount, channel equalization processing is performed for the cost function with the MISO-VSS-MCMA method to reduce the damage of network intrusion to the channel. Simulation results show that in node transmission channel equalization after network intrusion, this algorithm can reduce the error bit rate of signal transmission in network, and provide a good ability of correcting phase deflection in the output constellation, thus avoiding the error bit distortion and channel damage caused by network intrusion to the signal with a good equalization effect. This algorithm provides stronger convergence and map concentration, which demonstrates that its anti-interference and signal recovery capabilities are better, so it improves the anti-attack ability of the network.

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A Variable Step Size Blind Equalization Algorithm Based on Gamma Distribution

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.457-458.961 ◽

2012 ◽

Vol 457-458 ◽

pp. 961-967

Author(s):

Xiang Zhao ◽

Jin Yong Sun ◽

Han Hong Tan

Keyword(s):

Gamma Distribution ◽

Blind Equalization ◽

Weight Vector ◽

Variable Step Size ◽

Constant Modulus Algorithm ◽

Step Size ◽

Equalization Algorithm ◽

Variable Step ◽

Mean Square Errors ◽

Better Than

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.

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