{"title":"基于lte蜂窝网络的具有QoS的服务切片策略","authors":"Peng Sun, H. Naser","doi":"10.1145/3267129.3267140","DOIUrl":null,"url":null,"abstract":"This paper introduces a service slicing strategy for managing Quality of Service in LTE-based cellular networks by managing resource blocks in the uplink direction based on resource pooling. An algorithm is devised to optimize and allocate resource blocks in the uplink direction based on longterm transmission history, channel conditions, and long-term fair share of resources among different service slices (classes). The proposed service slicing mechanism can flexibly allocate network resources between different service slices. It offers an ultra-reliable low-latency service suitable for uRLLC applications, and low to medium latency services suitable for extreme mobile broadband (xMBB) and massive Internet of Things (mIoT) use cases in future 5G networks. One important merit of the proposed algorithm is that its performance does not vary with the Transmission Time Interval (TTI). This enables network designers to choose different values for TTI to achieve other design goals (such as improved powerefficiency or capacity gain) without affecting QoS.","PeriodicalId":369459,"journal":{"name":"Q2S and Security for Wireless and Mobile Networks","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Service Slicing Strategy with QoS for LTE-based Cellular Networks\",\"authors\":\"Peng Sun, H. Naser\",\"doi\":\"10.1145/3267129.3267140\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces a service slicing strategy for managing Quality of Service in LTE-based cellular networks by managing resource blocks in the uplink direction based on resource pooling. An algorithm is devised to optimize and allocate resource blocks in the uplink direction based on longterm transmission history, channel conditions, and long-term fair share of resources among different service slices (classes). The proposed service slicing mechanism can flexibly allocate network resources between different service slices. It offers an ultra-reliable low-latency service suitable for uRLLC applications, and low to medium latency services suitable for extreme mobile broadband (xMBB) and massive Internet of Things (mIoT) use cases in future 5G networks. One important merit of the proposed algorithm is that its performance does not vary with the Transmission Time Interval (TTI). This enables network designers to choose different values for TTI to achieve other design goals (such as improved powerefficiency or capacity gain) without affecting QoS.\",\"PeriodicalId\":369459,\"journal\":{\"name\":\"Q2S and Security for Wireless and Mobile Networks\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Q2S and Security for Wireless and Mobile Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3267129.3267140\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Q2S and Security for Wireless and Mobile Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3267129.3267140","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Service Slicing Strategy with QoS for LTE-based Cellular Networks
This paper introduces a service slicing strategy for managing Quality of Service in LTE-based cellular networks by managing resource blocks in the uplink direction based on resource pooling. An algorithm is devised to optimize and allocate resource blocks in the uplink direction based on longterm transmission history, channel conditions, and long-term fair share of resources among different service slices (classes). The proposed service slicing mechanism can flexibly allocate network resources between different service slices. It offers an ultra-reliable low-latency service suitable for uRLLC applications, and low to medium latency services suitable for extreme mobile broadband (xMBB) and massive Internet of Things (mIoT) use cases in future 5G networks. One important merit of the proposed algorithm is that its performance does not vary with the Transmission Time Interval (TTI). This enables network designers to choose different values for TTI to achieve other design goals (such as improved powerefficiency or capacity gain) without affecting QoS.