How Much Will Tiny IoT Nodes Profit from Massive Base Station Arrays?

Ema Becirovic, Emil Björnson, E. Larsson
{"title":"How Much Will Tiny IoT Nodes Profit from Massive Base Station Arrays?","authors":"Ema Becirovic, Emil Björnson, E. Larsson","doi":"10.23919/EUSIPCO.2018.8553057","DOIUrl":null,"url":null,"abstract":"In this paper we study the benefits that Internet-of-Things (IoT) devices will have from connecting to a massive multiple-input-multiple-output (MIMO) base station. In particular, we study how many users that could be simultaneously spatially multiplexed and how much the range can be increased by deploying massive base station arrays. We also investigate how the devices can scale down their uplink power as the number of antennas grows with retained rates. We consider the uplink and utilize upper and lower bounds on known achievable rate expressions to study the effects of the massive arrays. We conduct a case study where we use simulations in the settings of existing IoT systems to draw realistic conclusions. We find that the gains which ultra narrowband systems get from utilizing massive MIMO are limited by the bandwidth and therefore those systems will not be able to spatially multiplex any significant number of users. We also conclude that the power scaling is highly dependent on the nominal signal-to-noise ratio (SNR) in the single-antenna case.","PeriodicalId":303069,"journal":{"name":"2018 26th European Signal Processing Conference (EUSIPCO)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 26th European Signal Processing Conference (EUSIPCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/EUSIPCO.2018.8553057","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

In this paper we study the benefits that Internet-of-Things (IoT) devices will have from connecting to a massive multiple-input-multiple-output (MIMO) base station. In particular, we study how many users that could be simultaneously spatially multiplexed and how much the range can be increased by deploying massive base station arrays. We also investigate how the devices can scale down their uplink power as the number of antennas grows with retained rates. We consider the uplink and utilize upper and lower bounds on known achievable rate expressions to study the effects of the massive arrays. We conduct a case study where we use simulations in the settings of existing IoT systems to draw realistic conclusions. We find that the gains which ultra narrowband systems get from utilizing massive MIMO are limited by the bandwidth and therefore those systems will not be able to spatially multiplex any significant number of users. We also conclude that the power scaling is highly dependent on the nominal signal-to-noise ratio (SNR) in the single-antenna case.
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
微型物联网节点将从大规模基站阵列中获利多少?
在本文中,我们研究了物联网(IoT)设备连接到大型多输入多输出(MIMO)基站所带来的好处。特别是,我们研究了有多少用户可以同时进行空间复用,以及通过部署大规模基站阵列可以增加多少范围。我们还研究了设备如何随着天线数量的增长和保留率的增加而缩小其上行功率。我们考虑上行链路,利用已知可达速率表达式的上下界来研究大规模阵列的影响。我们进行了一个案例研究,在现有物联网系统的设置中使用模拟来得出现实的结论。我们发现,超窄带系统利用大规模MIMO获得的增益受到带宽的限制,因此这些系统将无法在空间上复用任何显著数量的用户。我们还得出结论,在单天线情况下,功率缩放高度依赖于标称信噪比(SNR)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Missing Sample Estimation Based on High-Order Sparse Linear Prediction for Audio Signals Multi-Shot Single Sensor Light Field Camera Using a Color Coded Mask Knowledge-Aided Normalized Iterative Hard Thresholding Algorithms for Sparse Recovery Two-Step Hybrid Multiuser Equalizer for Sub-Connected mmWave Massive MIMO SC-FDMA Systems How Much Will Tiny IoT Nodes Profit from Massive Base Station Arrays?
×
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