{"title":"OFDMA下行链路的VoIP容量模型","authors":"Patrick Hosein","doi":"10.1109/VETECF.2007.382","DOIUrl":null,"url":null,"abstract":"In traditional wireless networks, voice service is supported with synchronous power controlled channels and hence latency requirements were easily met. Fourth generation networks (3GPP2, 3GPP, WiMAX), are packet based and use orthogonal frequency division multiple access (OFDMA) on the forward link. In this case voice will typically be transported using the voice over IP (VoIP) protocol. With this approach, there is a trade-off between delay performance and user capacity since by using queuing one can more efficiently utilize radio resources but at the expense of additional queuing delays. In this paper we provide models for determining various performance metrics of such a system and compare the accuracy of the models with published simulation results. These models can be used to develop an intuitive understanding of the underlying performance as well as for performing sensitivity analysis.","PeriodicalId":261917,"journal":{"name":"2007 IEEE 66th Vehicular Technology Conference","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"VoIP Capacity Model for an OFDMA Downlink\",\"authors\":\"Patrick Hosein\",\"doi\":\"10.1109/VETECF.2007.382\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In traditional wireless networks, voice service is supported with synchronous power controlled channels and hence latency requirements were easily met. Fourth generation networks (3GPP2, 3GPP, WiMAX), are packet based and use orthogonal frequency division multiple access (OFDMA) on the forward link. In this case voice will typically be transported using the voice over IP (VoIP) protocol. With this approach, there is a trade-off between delay performance and user capacity since by using queuing one can more efficiently utilize radio resources but at the expense of additional queuing delays. In this paper we provide models for determining various performance metrics of such a system and compare the accuracy of the models with published simulation results. These models can be used to develop an intuitive understanding of the underlying performance as well as for performing sensitivity analysis.\",\"PeriodicalId\":261917,\"journal\":{\"name\":\"2007 IEEE 66th Vehicular Technology Conference\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE 66th Vehicular Technology Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VETECF.2007.382\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE 66th Vehicular Technology Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VETECF.2007.382","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In traditional wireless networks, voice service is supported with synchronous power controlled channels and hence latency requirements were easily met. Fourth generation networks (3GPP2, 3GPP, WiMAX), are packet based and use orthogonal frequency division multiple access (OFDMA) on the forward link. In this case voice will typically be transported using the voice over IP (VoIP) protocol. With this approach, there is a trade-off between delay performance and user capacity since by using queuing one can more efficiently utilize radio resources but at the expense of additional queuing delays. In this paper we provide models for determining various performance metrics of such a system and compare the accuracy of the models with published simulation results. These models can be used to develop an intuitive understanding of the underlying performance as well as for performing sensitivity analysis.