mMTC 5G NR (New Radio) Femtocells新实现的资源块(RB)分配方案在NS-3模拟器上的性能评估

Ismail Angri, A. Najid, Mohammed Mahfoudi
{"title":"mMTC 5G NR (New Radio) Femtocells新实现的资源块(RB)分配方案在NS-3模拟器上的性能评估","authors":"Ismail Angri, A. Najid, Mohammed Mahfoudi","doi":"10.1109/CloudTech49835.2020.9365883","DOIUrl":null,"url":null,"abstract":"The new standard of mobile technologies called 5G allows enormous improvements, comparing to the previous telecommunication network system LTE, in terms of user requirements by offering different use cases (eMBB, URLLC and mMTC). With the use of the Internet of Things (IoT) by 5G networks, the number of radio devices by each user will drop from 2 to around 7 to 10 devices. Despite this, the saturation of the system does not arise, thanks to the connected equipment’s high density, offered by Massive machine type communications (mMTC). A Radio Resource Management RRM procedure for efficient distribution of available radio resources between those devices is essential for 5G systems. In this article, we have studied the behavior of scheduling algorithms in a 5G environment, for a large number of connected objects and for different types of data flows, while limiting to small cells (Femtocells) with a speed of 3 km/h of the User Equipment (UE). In this objective, we program in C++ two new scheduling algorithms at the base station gNb, namely Exponential PF (EXP/PF) and Exponential Rule (EXP-rule), in addition to those already existing (Maximum-Weight (MW) and Proportional Fair (PF)), using the mmWave model of the famous NS-3 simulator. The performance comparison of the different 5G scheduler schemes was inspected via two important parameters, which are the user throughput and the Signal-to-Interference-plus-Noise Ratio (SINR). Consequently, we have demonstrated that the scheduling algorithms used by LTE networks can be implemented at the 5G gNB level. The results of our simulations have shown that the EXP-rule algorithm provides the best SINR and DataRate values for voice, video and data streams.","PeriodicalId":272860,"journal":{"name":"2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)","volume":"281 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Performance Evaluation of Newly Implemented Resource Blocks (RB) Allocation Schemes on NS-3 simulator for mMTC 5G NR (New Radio) Femtocells\",\"authors\":\"Ismail Angri, A. Najid, Mohammed Mahfoudi\",\"doi\":\"10.1109/CloudTech49835.2020.9365883\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The new standard of mobile technologies called 5G allows enormous improvements, comparing to the previous telecommunication network system LTE, in terms of user requirements by offering different use cases (eMBB, URLLC and mMTC). With the use of the Internet of Things (IoT) by 5G networks, the number of radio devices by each user will drop from 2 to around 7 to 10 devices. Despite this, the saturation of the system does not arise, thanks to the connected equipment’s high density, offered by Massive machine type communications (mMTC). A Radio Resource Management RRM procedure for efficient distribution of available radio resources between those devices is essential for 5G systems. In this article, we have studied the behavior of scheduling algorithms in a 5G environment, for a large number of connected objects and for different types of data flows, while limiting to small cells (Femtocells) with a speed of 3 km/h of the User Equipment (UE). In this objective, we program in C++ two new scheduling algorithms at the base station gNb, namely Exponential PF (EXP/PF) and Exponential Rule (EXP-rule), in addition to those already existing (Maximum-Weight (MW) and Proportional Fair (PF)), using the mmWave model of the famous NS-3 simulator. The performance comparison of the different 5G scheduler schemes was inspected via two important parameters, which are the user throughput and the Signal-to-Interference-plus-Noise Ratio (SINR). Consequently, we have demonstrated that the scheduling algorithms used by LTE networks can be implemented at the 5G gNB level. The results of our simulations have shown that the EXP-rule algorithm provides the best SINR and DataRate values for voice, video and data streams.\",\"PeriodicalId\":272860,\"journal\":{\"name\":\"2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)\",\"volume\":\"281 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CloudTech49835.2020.9365883\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CloudTech49835.2020.9365883","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

与之前的电信网络系统LTE相比,被称为5G的移动技术新标准通过提供不同的用例(eMBB、URLLC和mMTC),在用户需求方面实现了巨大的改进。随着5G网络使用物联网(IoT),每个用户的无线电设备数量将从2个减少到7到10个左右。尽管如此,由于大型机器类型通信(mMTC)提供的连接设备的高密度,系统不会出现饱和。用于在这些设备之间有效分配可用无线电资源的无线电资源管理RRM程序对于5G系统至关重要。在本文中,我们研究了5G环境下调度算法的行为,针对大量连接对象和不同类型的数据流,同时仅限于用户设备(UE)速度为3公里/小时的小蜂窝(Femtocells)。在此目标中,我们利用著名的NS-3模拟器的毫米波模型,在已有的调度算法(最大权重(MW)和比例公平(PF))的基础上,用c++编程了两种新的基站gNb调度算法,即指数PF (EXP/PF)和指数规则(EXP- Rule)。通过两个重要参数,即用户吞吐量和信噪比(SINR),对不同的5G调度方案进行了性能比较。因此,我们已经证明了LTE网络使用的调度算法可以在5G gNB级别上实现。仿真结果表明EXP-rule算法为语音、视频和数据流提供了最佳的SINR和DataRate值。
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
Performance Evaluation of Newly Implemented Resource Blocks (RB) Allocation Schemes on NS-3 simulator for mMTC 5G NR (New Radio) Femtocells
The new standard of mobile technologies called 5G allows enormous improvements, comparing to the previous telecommunication network system LTE, in terms of user requirements by offering different use cases (eMBB, URLLC and mMTC). With the use of the Internet of Things (IoT) by 5G networks, the number of radio devices by each user will drop from 2 to around 7 to 10 devices. Despite this, the saturation of the system does not arise, thanks to the connected equipment’s high density, offered by Massive machine type communications (mMTC). A Radio Resource Management RRM procedure for efficient distribution of available radio resources between those devices is essential for 5G systems. In this article, we have studied the behavior of scheduling algorithms in a 5G environment, for a large number of connected objects and for different types of data flows, while limiting to small cells (Femtocells) with a speed of 3 km/h of the User Equipment (UE). In this objective, we program in C++ two new scheduling algorithms at the base station gNb, namely Exponential PF (EXP/PF) and Exponential Rule (EXP-rule), in addition to those already existing (Maximum-Weight (MW) and Proportional Fair (PF)), using the mmWave model of the famous NS-3 simulator. The performance comparison of the different 5G scheduler schemes was inspected via two important parameters, which are the user throughput and the Signal-to-Interference-plus-Noise Ratio (SINR). Consequently, we have demonstrated that the scheduling algorithms used by LTE networks can be implemented at the 5G gNB level. The results of our simulations have shown that the EXP-rule algorithm provides the best SINR and DataRate values for voice, video and data streams.
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
CloudTech 2020 Copyright Page An IoT data logging instrument for monitoring and early efficiency loss detection at a photovoltaic generation plant A cloud-based foundational infrastructure for water management ecosystem Medical Image Registration via Similarity Measure based on Convolutional Neural Network Quality Approach to Analyze the Causes of Failures in MOOC
×
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