Title :
A Neural Network Blind Multi-user Detection Algorithm
Author_Institution :
Coll. of Technol., Taiyuan Univ. of Technol., Taiyuan, China
Abstract :
This paper proposed a blind multi-user detection algorithm based on neural network. The constant modulus cost function was constructed and cost function with restricted condition was optimized by augmented Lagrange method. Iterative formula of neural network weight and parameters were deduced by least mean square. Blind multi-user detection can be realized by iterative functions of neural network. Simulation indicates the new algorithm improves the ability of anti-MAI., reduces error rate, and speeds up convergence rate.
Keywords :
code division multiple access; feedforward neural nets; iterative methods; least mean squares methods; multiuser detection; telecommunication computing; CDMA; augmented Lagrange method; blind multiuser detection algorithm; code division multiple access; constant modulus cost function; feedforward neural network; iterative formula; least mean square method; Convergence; Cost function; Feedforward systems; Iterative algorithms; Mechatronics; Multiaccess communication; Multiuser detection; Neural networks; Paper technology; Transfer functions; blind multi-user detection algorithm; cost function; neural network;
Conference_Titel :
Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on
Conference_Location :
Zhangjiajie, Hunan
Print_ISBN :
978-0-7695-3583-8
DOI :
10.1109/ICMTMA.2009.92
