Title :
Neural networks for multi-user detection in MC-CDMA systems
Author :
Carlier, Florent ; Nouvel, Fabienne
Author_Institution :
Inst. of Electron. & Telecommun., CNRS, Rennes, France
Abstract :
This paper presents a MC-CDMA detector based on unsupervised neural network. As systems based on MC-CDMA techniques require complex implementation to achieve high data rates, we propose a solution with lower complexity, and realtime execution. The underlying idea is to allow a simulated system to be implemented on a realtime system in the field of standard multi-user detection methods.
Keywords :
code division multiple access; computational complexity; mobile radio; multiuser detection; neural nets; telecommunication computing; MC-CDMA systems; complexity; mobile radio systems; multiple access-code division multiple access; multiuser detection methods; neural networks; realtime system; Additive white noise; Detectors; Gaussian noise; Intelligent networks; Interference cancellation; Multiaccess communication; Multicarrier code division multiple access; Multiuser detection; Neural networks; Spread spectrum communication;
Conference_Titel :
Vehicular Technology Conference, 2003. VTC 2003-Spring. The 57th IEEE Semiannual
Print_ISBN :
0-7803-7757-5
DOI :
10.1109/VETECS.2003.1208820
