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ROLS-AWS Algorithm Used in RBF Neural Network Multiuser Detection


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ROLS-AWS Algorithm Used in RBF Neural Network Multiuser Detection
WANG Yong-jian ZHOU Ting-xian
The Research Center of Communications,Harbin Institute of Technology, Harbin 150001,China
multiuser detect ion mult iple access interference RBF neural network ROLS-AWS algorithm
In order to suppress the multiple access interference ( MAI) and resist near-far ef fect, the recursive orthogonal least square w ith auto w eight select ion ( ROLS-AWS) alg orithm used in radial basis funct ion( RBF) neural netw ork is int roduced to the multiuser detection( MUD) . T he paper f irst int roduces RBF into MU D. Then the three-layer neural netw ork demodulation spread-spectrum signal model in synchronous Gauss channel w as given. The mult-i user detection receiver was analyzed. In order to improve the computat ional speed, the ROLS-AWS algorithm was used in the RBF-based MUD receiver. The simulated results show that the proposed RBF-based MUD receiver using ROLS-AWS algorithm is better than the conventional detector, the common BP and the RBF neural network which does not use ROLS-AWS based MUD receiver on suppressing multiple access interference, near-far effect and training speed.


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Last Update: 2013-05-23