LTE下行链路调度:一个真正的贝叶斯估计方法

Khairul Anwar Bin Kamarul Hatta, K. Wee, W. Cheah, Y. Wee
{"title":"LTE下行链路调度:一个真正的贝叶斯估计方法","authors":"Khairul Anwar Bin Kamarul Hatta, K. Wee, W. Cheah, Y. Wee","doi":"10.12720/jcm.17.11.865-877","DOIUrl":null,"url":null,"abstract":"Extended research has been made in exploring the possibilities of a better real-time oriented downlink scheduling. The reason for these possibilities is caused by a fast-paced growth demand for multimedia applications that are mainly developed for mobile devices, and requires a high-speed wireless transmission for its satisfaction. Repositioning mobile devices have been one of the challenges arising from that demand. Due to the growth of mobile device users, another challenge has also been found, which is the capability of wireless networks to handle multiple simultaneous users within a single cell network environment. Current downlink scheduling algorithm which can cope with this challenge, Most Largest Weighted Delay First (MLWDF), needs to be improvised to suits the demands. True Bayesian Estimate (TBE) is one of the Bayes Estimator models which is suitable for handling multivariate parameters. Three proposed TBE algorithms have been designed with each having a different key design and objective. TBE-Fair (TBE-F) has provided a fairer and less delay scheduling as compared to MLWDF while TBE-Delay (TBE-D) manages to have a higher throughput rate. TBE-Flow Delay (TBE-FD) is an overall scheduler that manages multivariate QoS to perform better for real-time scheduling. All the TBE’s algorithms have better performances than MLWDF in real-time traffic due to its main key design of real-time oriented scheduling which focuses more on video and VoIP flows.","PeriodicalId":14832,"journal":{"name":"J. Comput. Mediat. Commun.","volume":"19 1","pages":"865-877"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"LTE Downlink Scheduling: A True Bayesian Estimate Approach\",\"authors\":\"Khairul Anwar Bin Kamarul Hatta, K. Wee, W. Cheah, Y. Wee\",\"doi\":\"10.12720/jcm.17.11.865-877\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Extended research has been made in exploring the possibilities of a better real-time oriented downlink scheduling. The reason for these possibilities is caused by a fast-paced growth demand for multimedia applications that are mainly developed for mobile devices, and requires a high-speed wireless transmission for its satisfaction. Repositioning mobile devices have been one of the challenges arising from that demand. Due to the growth of mobile device users, another challenge has also been found, which is the capability of wireless networks to handle multiple simultaneous users within a single cell network environment. Current downlink scheduling algorithm which can cope with this challenge, Most Largest Weighted Delay First (MLWDF), needs to be improvised to suits the demands. True Bayesian Estimate (TBE) is one of the Bayes Estimator models which is suitable for handling multivariate parameters. Three proposed TBE algorithms have been designed with each having a different key design and objective. TBE-Fair (TBE-F) has provided a fairer and less delay scheduling as compared to MLWDF while TBE-Delay (TBE-D) manages to have a higher throughput rate. TBE-Flow Delay (TBE-FD) is an overall scheduler that manages multivariate QoS to perform better for real-time scheduling. All the TBE’s algorithms have better performances than MLWDF in real-time traffic due to its main key design of real-time oriented scheduling which focuses more on video and VoIP flows.\",\"PeriodicalId\":14832,\"journal\":{\"name\":\"J. Comput. Mediat. Commun.\",\"volume\":\"19 1\",\"pages\":\"865-877\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"J. Comput. Mediat. Commun.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12720/jcm.17.11.865-877\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Comput. Mediat. Commun.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12720/jcm.17.11.865-877","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

在探索一种更好的面向实时的下行链路调度的可能性方面进行了扩展研究。出现这些可能性的原因是主要为移动设备开发的多媒体应用程序的需求快速增长,并且需要高速无线传输来满足其需求。重新定位移动设备是这种需求带来的挑战之一。由于移动设备用户的增长,还发现了另一个挑战,即无线网络在单个蜂窝网络环境中处理多个同时用户的能力。目前能够应对这一挑战的下行链路调度算法——最大加权延迟优先算法(MLWDF)需要改进以适应需求。真贝叶斯估计(True Bayesian estimation, TBE)是一种适合处理多变量参数的贝叶斯估计模型。提出了三种TBE算法,每种算法都有不同的关键设计和目标。与MLWDF相比,TBE-Fair (TBE-F)提供了更公平和更少延迟的调度,而TBE-Delay (TBE-D)设法具有更高的吞吐率。TBE-Flow Delay (TBE-FD)是一个整体调度程序,它管理多变量QoS,以便更好地执行实时调度。所有的TBE算法都比MLWDF算法在实时流量方面有更好的性能,因为它的主要关键设计是面向实时的调度,更关注视频和VoIP流。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
LTE Downlink Scheduling: A True Bayesian Estimate Approach
Extended research has been made in exploring the possibilities of a better real-time oriented downlink scheduling. The reason for these possibilities is caused by a fast-paced growth demand for multimedia applications that are mainly developed for mobile devices, and requires a high-speed wireless transmission for its satisfaction. Repositioning mobile devices have been one of the challenges arising from that demand. Due to the growth of mobile device users, another challenge has also been found, which is the capability of wireless networks to handle multiple simultaneous users within a single cell network environment. Current downlink scheduling algorithm which can cope with this challenge, Most Largest Weighted Delay First (MLWDF), needs to be improvised to suits the demands. True Bayesian Estimate (TBE) is one of the Bayes Estimator models which is suitable for handling multivariate parameters. Three proposed TBE algorithms have been designed with each having a different key design and objective. TBE-Fair (TBE-F) has provided a fairer and less delay scheduling as compared to MLWDF while TBE-Delay (TBE-D) manages to have a higher throughput rate. TBE-Flow Delay (TBE-FD) is an overall scheduler that manages multivariate QoS to perform better for real-time scheduling. All the TBE’s algorithms have better performances than MLWDF in real-time traffic due to its main key design of real-time oriented scheduling which focuses more on video and VoIP flows.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
To intervene or not to intervene: young adults' views on when and how to intervene in online harassment Effect of Parasitic Patch for the Radiation Characteristics Microstrip Antenna Planar Array with Distribution Edge An Optimized Vertical Handover Decision Model for the Heterogeneous DSRC/LTE Vehicular Networks Performance Evaluation of Optical Amplifiers in a Hybrid RoF-WDM Communication System A Non-hierarchical Multipath Routing Protocol Using Fuzzy Logic for Optimal Network Lifetime in Wireless Sensor Network
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1