|Table of Contents|

ROLS-AWS Algorithm Used in RBF Neural Network Multiuser Detection

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2005年02期
Page:
197-201
Research Field:
Publishing date:

Info

Title:
ROLS-AWS Algorithm Used in RBF Neural Network Multiuser Detection
Author(s):
WANG Yong-jian ZHOU Ting-xian
The Research Center of Communications,Harbin Institute of Technology, Harbin 150001,China
Keywords:
multiuser detect ion mult iple access interference RBF neural network ROLS-AWS algorithm
PACS:
TN929.533
DOI:
-
Abstract:
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.

References:

[ 1] Lupas R, Ver du S. Linear Multiuser detectors fo r synchronous code- div ision mult iple- access channels [ J ] . IEEE Tr ans I nfo Theor y, 1989, 35( 1) : 123- 136.
[ 2 ] Var anasi M K, Aazhang B. Mult-i stag e detection in asynchronous code- division multiple- access channels [ J] . IEEE Trans Commun, 1990, 38: 509- 519.
[ 3] Duelha. A family of multiuser decision feedback detectors for asynchronous code division multiple access channels [ J] . IEEE Trans Commun, 1995, 43: 421- 434.
[ 4] Behnaam A, Ber nd- Peter P, Geoffrey C O. Neural netwo rks for mult iuser detection in code- div ision multiple- access communication[ J] . IEEE Trans Commun, 1992, 40 ( 7) : 1 212- 1 222.
[ 5] Mitra U, Vincent P. Neural network technique for adaptiv e multiuser demodulation[ J] . IEEE Journal on Selected Ar eas in Communications, 1994, 12 ( 9) : 1 460 - 1 470.
[ 6] 刘明雷, 周廷显. RBF 神经网络CDMA 多用户检测方法. 通信技术. 2003( 11) : 54- 56.
[ 7] Meng H, Fun M, Hagan T . Recursive or thogonal least squares learning w ith automatic w eight selection for Gaussian neural networks [ EB/ OL] . http: / / w ww. hagan. ecen. ceat. okstate. edu. 1999.
[ 8] Chen S, Cow anCFN, G. Ortho gonal least squares learning algorithm for radial basis function networks [ J ] . IEEE Trans Neural Networks, 1991, 2( 2) : 302- 308.

Memo

Memo:
-
Last Update: 2013-05-23