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