DocumentCode :
2253497
Title :
DS-CDMA MAI-cancellation using hysteretic Hopfield neural networks
Author :
Soujeri, Ebrahim Ali
Author_Institution :
Dept. of E.E. Eng., Eur. Univ. of Lefke, Gemikonagi
fYear :
2006
fDate :
16-19 May 2006
Firstpage :
660
Lastpage :
663
Abstract :
Multi-user interference cancellation (MAI) using hysteretic Hopfield neural network (HHNN) receiver for direct sequence code-division multiple access (DS-CDMA) in multipath fading (MPF) channels is investigated. We have shown that by applying the phenomenon of "hysteresis" to the HNN detector, we may enhance the performance of this detector in all near-far situations, for different number of multipath rays. The introduction of hysteresis concept into HNN has made the CDMA HNN detector (which we shall call the HHNN detector) even closer to the CDMA optimum multiuser detector. As shown by simulation results, the BER performance achieved by the HHNN detector outperforms the classical HNN detector with a good margin and is promising
Keywords :
Hopfield neural nets; code division multiple access; error statistics; fading channels; interference suppression; multipath channels; multiuser detection; spread spectrum communication; telecommunication computing; BER performance; CDMA HNN detector; CDMA optimum multiuser detector; DS-CDMA MAI-cancellation; direct sequence code-division multiple access; hysteretic Hopfield neural networks; multi-user interference cancellation; multipath fading channels; multipath rays; Binary phase shift keying; Bit error rate; Detectors; Fading; Hopfield neural networks; Hysteresis; Interference cancellation; Multiaccess communication; Multiple access interference; Transmitters;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrotechnical Conference, 2006. MELECON 2006. IEEE Mediterranean
Conference_Location :
Malaga
Print_ISBN :
1-4244-0087-2
Type :
conf
DOI :
10.1109/MELCON.2006.1653186
Filename :
1653186
Link To Document :
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