Adaptive Near-Optimal Multiuser Detection Using a Stochastic and Hysteretic Hopfield Net Receiver

Autor: Gábor Jeney, János Levendovszky, E. C. van der Meulen, László Pap
Jazyk: angličtina
Rok vydání: 2003
Předmět:
Zdroj: EURASIP Journal on Advances in Signal Processing, Vol 2002, Iss 12, Pp 1401-1414 (2003)
Druh dokumentu: article
ISSN: 16876172
1687-6172
1687-6180
DOI: 10.1155/S1110865702209130
Popis: This paper proposes a novel adaptive MUD algorithm for a wide variety (practically any kind) of interference limited systems, for example, code division multiple access (CDMA). The algorithm is based on recently developed neural network techniques and can perform near optimal detection in the case of unknown channel characteristics. The proposed algorithm consists of two main blocks; one estimates the symbols sent by the transmitters, the other identifies each channel of the corresponding communication links. The estimation of symbols is carried out either by a stochastic Hopfield net (SHN) or by a hysteretic neural network (HyNN) or both. The channel identification is based on either the self-organizing feature map (SOM) or the learning vector quantization (LVQ). The combination of these two blocks yields a powerful real-time detector with near optimal performance. The performance is analyzed by extensive simulations.
Databáze: Directory of Open Access Journals
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