Blind channel equalization in the presence of co-channel interference using higher order statistics

2017 ◽  
Author(s):  
Balagobalan Kapilan ◽  
Guohua Wang ◽  
Sirajudeen Gulam Razul ◽  
Shang Kee Ting ◽  
Chong Meng See
Keyword(s):  
Order Statistics ◽  
Channel Equalization ◽  
Higher Order ◽  
Higher Order Statistics ◽  
Blind Channel Equalization ◽  
Blind Channel ◽  
Channel Interference

scholarly journals Blind Channel Estimation for STBC Systems Using Higher-Order Statistics

2011 ◽  
Vol 10 (2) ◽  
pp. 495-505 ◽  
Author(s):  
Vincent Choqueuse ◽  
Ali Mansour ◽  
Gilles Burel ◽  
Ludovic Collin ◽  
Koffi Yao
Keyword(s):  
Channel Estimation ◽  
Order Statistics ◽  
Higher Order ◽  
Blind Channel Estimation ◽  
Higher Order Statistics ◽  
Blind Channel

Blind Equalization in the Presence of Co-channel Interference Based on Higher-Order Statistics

2018 ◽  
Vol 37 (9) ◽  
pp. 4150-4161
Author(s):  
Guohua Wang ◽  
Balagobalan Kapilan ◽  
Sirajudeen Gulam Razul ◽  
Shang Kee Ting ◽  
Chong Meng Samson See
Keyword(s):  
Order Statistics ◽  
Blind Equalization ◽  
Higher Order ◽  
Higher Order Statistics ◽  
Channel Interference

scholarly journals Effects of blind channel equalization using the regressive accelerator algorithm version ɣ

2018 ◽  
Vol 16 (46) ◽  
pp. 9-20
Author(s):  
Johanna Andrea Hurtado Sánchez ◽  
Pablo Emilio Jojoa Gómez
Keyword(s):  
Mean Square Error ◽  
Minimum Mean Square Error ◽  
Optimal Estimation ◽  
Channel Equalization ◽  
Higher Order ◽  
Stochastic Gradient ◽  
Mean Square ◽  
Blind Channel Equalization ◽  
Blind Channel ◽  
Transmitted Signal

We present a blind channel equalization scheme, applied to ɣ version regressive acceleration algorithm, which uses self-taught equalization techniques to study the characteristics of both, the second and the higher order moments for the transmitted signal, used to calculate the signal of error and thus, to make an optimal estimation of the transmitted symbols. This way, simulations of the obtained results are done in comparison with the algorithms based on the stochastic gradient and with the Bussgang algorithms. The results of that simulations show how, using the regressive acceleration algorithm version ɣ, a better detection of transmitted bits and higher convergence speeds are obtained, with a minimum mean square error.

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