DocumentCode :
485219
Title :
A novel feed-forward neural network blind multi-user detection algorithm by augmented Lagrange optimization
Author :
Sun Yunshan ; Li Yanqin ; Jia Fengmei ; Liu Ting ; Zhang Liyi ; Zhang Yan
Author_Institution :
Coll. of Inf. Eng., Tianjin Univ. of Commerce, Tianjin
fYear :
2007
fDate :
12-14 Dec. 2007
Firstpage :
8
Lastpage :
11
Abstract :
A feed-forward neural network blind multi-user detection algorithm was proposed. Feed-forward neural network and constant modulus algorithm (CMA) were consociated to complete blind multi-user detection. A constant modulus cost function firstly was constructed and the cost function with restrict condition was optimized by augmented Lagrange method. Blind multi-user detection algorithm was realized by iterative equations of FNN. And computer simulation indicates the new algorithm improves the ability to overcome MAI and makes bit error ratio lower.
Keywords :
feedforward neural nets; iterative methods; multiuser detection; optimisation; augmented Lagrange optimization; blind multiuser detection algorithm; constant modulus algorithm; constant modulus cost function; feedforward neural network; iterative equation; blind multi-user detection (BMUD); constant model algorithm; cost function; feed-forward neural network (FNN);
fLanguage :
English
Publisher :
iet
Conference_Titel :
Wireless, Mobile and Sensor Networks, 2007. (CCWMSN07). IET Conference on
Conference_Location :
Shanghai
ISSN :
0537-9989
Print_ISBN :
978-0-86341-836-5
Type :
conf
Filename :
4786124
Link To Document :
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