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dc.contributor.authorFang, YGen_US
dc.contributor.authorChlamtac, Ien_US
dc.contributor.authorLin, YBen_US
dc.date.accessioned2014-12-08T15:01:16Z-
dc.date.available2014-12-08T15:01:16Z-
dc.date.issued1997-12-01en_US
dc.identifier.issn1063-6692en_US
dc.identifier.urihttp://dx.doi.org/10.1109/90.650148en_US
dc.identifier.urihttp://hdl.handle.net/11536/156-
dc.description.abstractIn a personal communication service (PCS) network, the call completion probability and the effective call holding times for both complete and incomplete calls are central parameters in the network cost/performance evaluation, These quantities will depend on the distributions of call holding times and cell residence times, The classical assumptions made in the past that call holding times and cell residence times are exponentially distributed are not appropriate for the emerging PCS networks, This paper presents some systematic results on the probability of call completion and the effective call holding time distributions for complete and incomplete calls with general cell residence times and call holding times distributed with various distributions such as Gamma, Erlang, hyperexponential, hyper-Erlaug, and other staged distributions, These results provide a set of alternatives for PCS network modeling, which can be chosen to accommodate the measured data from PCS field trials, The application of these results in billing rate planning is also discussed.en_US
dc.language.isoen_USen_US
dc.subjectbilling rate planningen_US
dc.subjectcall blockingen_US
dc.subjectcall holding timeen_US
dc.subjectcall terminationen_US
dc.subjectcell residenceen_US
dc.subjecthandoffen_US
dc.subjectPCSen_US
dc.titleModeling PCS networks under general call holding time and cell residence time distributionsen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/90.650148en_US
dc.identifier.journalIEEE-ACM TRANSACTIONS ON NETWORKINGen_US
dc.citation.volume5en_US
dc.citation.issue6en_US
dc.citation.spage893en_US
dc.citation.epage906en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000071721400013-
dc.citation.woscount68-
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