毫米波大规模MIMO-NOMA系统中基于方位的聚类算法

Hua He, Yanxia Liang, Shulei Li
{"title":"毫米波大规模MIMO-NOMA系统中基于方位的聚类算法","authors":"Hua He, Yanxia Liang, Shulei Li","doi":"10.1109/ICCCWorkshops52231.2021.9538933","DOIUrl":null,"url":null,"abstract":"In order to resolve the massive access in future generation, NOMA (non-orthogonal multiple access) is exploited in the Massive MIMO communication system at the mmWave (millimeter wave) frequency to gain a very high capacity and access a very large number of users. The user clustering is key issue, which give impact to the performance of the system. Due to the directional transmission at mmWave frequency and space multiplexing of Massive MIMO, we propose k-means clustering algorithm based on azimuth, which takes use of the user’s azimuth to group users with the similar azimuths into the same cluster, while users with distinct azimuths into the different clusters. It cannot only increase the access number from spatial aspect, and also reduce the inter-cluster interference. The simulation results show that the proposed algorithms can realize directional clustering, which well achieves the desired goal.","PeriodicalId":335240,"journal":{"name":"2021 IEEE/CIC International Conference on Communications in China (ICCC Workshops)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Clustering Algorithm based on Azimuth in MmWave Massive MIMO-NOMA System\",\"authors\":\"Hua He, Yanxia Liang, Shulei Li\",\"doi\":\"10.1109/ICCCWorkshops52231.2021.9538933\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to resolve the massive access in future generation, NOMA (non-orthogonal multiple access) is exploited in the Massive MIMO communication system at the mmWave (millimeter wave) frequency to gain a very high capacity and access a very large number of users. The user clustering is key issue, which give impact to the performance of the system. Due to the directional transmission at mmWave frequency and space multiplexing of Massive MIMO, we propose k-means clustering algorithm based on azimuth, which takes use of the user’s azimuth to group users with the similar azimuths into the same cluster, while users with distinct azimuths into the different clusters. It cannot only increase the access number from spatial aspect, and also reduce the inter-cluster interference. The simulation results show that the proposed algorithms can realize directional clustering, which well achieves the desired goal.\",\"PeriodicalId\":335240,\"journal\":{\"name\":\"2021 IEEE/CIC International Conference on Communications in China (ICCC Workshops)\",\"volume\":\"99 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE/CIC International Conference on Communications in China (ICCC Workshops)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCWorkshops52231.2021.9538933\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE/CIC International Conference on Communications in China (ICCC Workshops)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCWorkshops52231.2021.9538933","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

为了解决下一代的海量接入问题,在mmWave(毫米波)频率的massive MIMO通信系统中采用了NOMA(非正交多址)技术,以获得非常高的容量和访问非常多的用户。用户聚类是影响系统性能的关键问题。针对Massive MIMO在毫米波频率下的定向传输和空间复用的特点,提出了基于方位角的k-means聚类算法,该算法利用用户的方位角将方位角相似的用户分组到同一簇中,将方位角不同的用户分组到不同簇中。它既能从空间上增加接入数,又能减少簇间干扰。仿真结果表明,所提算法能够实现定向聚类,较好地达到了预期目标。
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
Clustering Algorithm based on Azimuth in MmWave Massive MIMO-NOMA System
In order to resolve the massive access in future generation, NOMA (non-orthogonal multiple access) is exploited in the Massive MIMO communication system at the mmWave (millimeter wave) frequency to gain a very high capacity and access a very large number of users. The user clustering is key issue, which give impact to the performance of the system. Due to the directional transmission at mmWave frequency and space multiplexing of Massive MIMO, we propose k-means clustering algorithm based on azimuth, which takes use of the user’s azimuth to group users with the similar azimuths into the same cluster, while users with distinct azimuths into the different clusters. It cannot only increase the access number from spatial aspect, and also reduce the inter-cluster interference. The simulation results show that the proposed algorithms can realize directional clustering, which well achieves the desired goal.
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
Link Reliability Prediction for Long-range Underwater Acoustic Communications between Gliders A Review of 3GPP Release 18 on Smart Energy and Infrastructure Analysis on Power Configuration in 5G Co-construction and Sharing Network Application of Passive Acoustic Technology in the Monitoring of Abalone’s Feeding Behavior Ultra-Compact Dual-Polarized Dipole Antenna for Ultra-Massive MIMO Systems
×
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