Blind MultiUser Detection Algrithem Based on LMK Feed-Foward Neural Network

Author

Hongbin, Wang ; Liyi, Zhang ; Huakui, Wang

Author_Institution

Dept. of Comput. Sci., XinZhou Teachers Univ., Xinzhou, China

Volume

2

fYear

2009

fDate

14-16 Aug. 2009

Firstpage

299

Lastpage

302

Abstract

A feed-forward neural network blind multi-user detection algorithm based on the minimum kurtosis criteria was proposed. According to the characteristics of higher order cumulants, the cost function based on the minimum kurtosis criteria is founded. Constraint condition ensures that the desired signal can be obtained. The constraint cost function is optimized by the optimal methods. The feed-forward neural network blind multi-user detection algorithm based on minimum kurtosis criteria is realized. Simulations show that the new algorithm is superior to the traditional linear constraints algorithm in BER and convergence speed.

Keywords

error statistics; feedforward neural nets; multi-access systems; multiuser detection; BER; bit error rate; blind multiuser detection algorithm; constraint condition; convergence speed; feedfoward neural network; linear constraints algorithm; minimum kurtosis criteria; Cost function; Electronic mail; Feedforward neural networks; Feedforward systems; Iterative algorithms; Iterative methods; Multiaccess communication; Multiple access interference; Multiuser detection; Neural networks; Least Mean Kurtosis (LMK); blind multi-user detection; feed-forward neural network; kurtosis criteria;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation, 2009. ICNC '09. Fifth International Conference on

Conference_Location

Tianjin

Print_ISBN

978-0-7695-3736-8

Type

conf

DOI

10.1109/ICNC.2009.470

Filename

5365759