Hopfield neural network and Viterbi decoding for asynchronous MC-CDMA communication systems

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dc.contributor.authorSoujeri, E
dc.contributor.authorBilgekul, H
dc.date.accessioned2026-02-06T18:16:41Z
dc.date.issued2000
dc.departmentDoğu Akdeniz Üniversitesi
dc.description12th International Conference on Microelectronics (ICM 2000) -- OCT 31-NOV 02, 2000 -- UNIV TEHRAN, TEHRAN, IRAN
dc.description.abstractHopfield neural network (HNN) multiuser detection in conjunction with Viterbi decoding of an asynchronous multicarrier code-division multiple-access (MC-CDMA) communication system is investigated. In this scenario, the noise is characterized as being the sum of other users interference and additive white Gaussian noise (AWGN). The optimal multiuser detector for CDMA has a complexity that is exponential in the number of users. Previous studies have shown that this detector can completely remove the multiple-access interference from the received signal. Convolutional encoding with Viterbi decoding is particularly suited to a channel in which the transmitted signal is corrupted mainly by AWGN. Simulation results indicate that the HNN detector with Viterbi decoding is a good alternative to matched filter detector.
dc.description.sponsorshipEmad Semicon Inc,Minist Energy,Minist Post, Telegraph and Telephone,Minist Sci, Res and Technol,Tehran Reg Power Co,Dev & Renewal Org Iran Ind,Electr Res & Dev Support Fund,Malek e Ashtar Univ Technol,Univ Tehran, Alumni Assoc Fac Engn,Islamic Republic Iran Broadcasting,Telecommun Co Iran,Engn & Construct Oil Ind Corp,Iran Commun Ind Inc,TAKTA,Railway Islamic Republic Iran
dc.identifier.doi10.1109/ICM.2000.916447
dc.identifier.endpage218
dc.identifier.isbn964-360-057-2
dc.identifier.issn1110-6972
dc.identifier.orcid0000-0002-3791-9358
dc.identifier.scopus2-s2.0-84979523506
dc.identifier.scopusqualityQ4
dc.identifier.startpage215
dc.identifier.urihttps://doi.org/10.1109/ICM.2000.916447
dc.identifier.urihttps://hdl.handle.net/11129/8606
dc.identifier.wosWOS:000170639300048
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIEEE Computer Soc
dc.relation.ispartofIcm 2000: Proceedings of the 12Th International Conference on Microelectronics
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260204
dc.subjectMulticarrier Cdma
dc.subjectFading Channel
dc.subjectPerformance
dc.titleHopfield neural network and Viterbi decoding for asynchronous MC-CDMA communication systems
dc.typeConference Object

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