DocumentCode :
1908160
Title :
Neural network techniques for multi-user demodulation
Author :
Mitra, U. ; Poor, H.V.
Author_Institution :
Dept. of Electr. Eng., Princeton Univ., NJ, USA
fYear :
1993
fDate :
1993
Firstpage :
1538
Abstract :
Adaptive methods for demodulating multi-user communication in a direct-sequence spread-spectrum multiple-access (DS/SSMA) environment are investigated. Adaptive radial basis function (RBF) networks that operate with knowledge of only a subset of the system parameters are studied. This approach is further bolstered by the fact that the optimal detector in the synchronous case can be implemented by an RBF network when all of the system parameters are known. The RBF network performance is compared with other multi-user detectors. The centers of the RBF neurons, when the system parameters are not fully known, are determined using clustering techniques. It is shown that the adaptive RBF network obtains near optimal performance and is robust in realistic communication environments
Keywords :
adaptive systems; demodulation; multi-access systems; neural nets; spread spectrum communication; telecommunications computing; adaptive radial basis function net; clustering; direct-sequence spread-spectrum multiple-access; multi-user communication; multi-user demodulation; neural nets; Additive noise; Decorrelation; Demodulation; Detectors; Gaussian noise; Matched filters; Maximum likelihood detection; Multiaccess communication; Neural networks; Radial basis function networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1993., IEEE International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-0999-5
Type :
conf
DOI :
10.1109/ICNN.1993.298785
Filename :
298785
Link To Document :
بازگشت