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Fuzzy/neural congestion control for integrated voice and data DS-CDMA/FRMA cellular networks

dc.citation.epage293en_US
dc.citation.issue2en_US
dc.citation.spage283en_US
dc.citation.volume18en_US
dc.citation.woscount9
dc.contributor.authorChang, CJen_US
dc.contributor.authorChen, BWen_US
dc.contributor.authorLiu, TYen_US
dc.contributor.authorRen, FCen_US
dc.contributor.department電信工程研究所zh_TW
dc.contributor.departmentInstitute of Communications Engineeringen_US
dc.date.accessioned2014-12-08T15:45:46Z
dc.date.available2014-12-08T15:45:46Z
dc.date.issued2000-02-01en_US
dc.description.abstractThe paper proposes congestion control using fuzzy/neural techniques for integrated voice and data direct-sequence code division multiple access/frame reservation multiple access (DS-CDMA/FRMA) cellular networks. The fuzzy/neural congestion controller is constituted by a pipeline recurrent neural network (PRNN) interference predictor, a fuzzy performance indicator, and a fuzzy/neural access probability controller It regulates traffic input to the integrated voice and data DS-CDMA/FRMA cellular system by determining proper access probabilities for users so that congestion can be avoided and throughput can be maximized. Simulation results show that the DS-CDMA/FRMA fuzzy/neural congestion controllers perform better than conventional DS-CDMA/PRMA with channel access function in voice packet dropping ratio, corruption ratio, and utilization. In addition, the neural congestion controller outperforms the fuzzy congestion controller.en_US
dc.identifier.doi10.1109/49.824814en_US
dc.identifier.issn0733-8716en_US
dc.identifier.journalIEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONSen_US
dc.identifier.urihttp://dx.doi.org/10.1109/49.824814en_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/30793
dc.identifier.wosnumberWOS:000085750500012
dc.language.isoen_USen_US
dc.subjectcongestion controlen_US
dc.subjectdirect sequence-code division multiple access/frame reservation multiple accessen_US
dc.subject(DS-CDMA/FRMA) cellular networksen_US
dc.subjectfuzzy/neural techniquesen_US
dc.titleFuzzy/neural congestion control for integrated voice and data DS-CDMA/FRMA cellular networksen_US
dc.typeArticleen_US

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