利用三层用户分组和自适应功率分配算法提高毫米波 MIMO-NOMA 的能效

IF 3.8 3区 计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
K. Ramesh Chandra , Somasekhar Borugadda
{"title":"利用三层用户分组和自适应功率分配算法提高毫米波 MIMO-NOMA 的能效","authors":"K. Ramesh Chandra ,&nbsp;Somasekhar Borugadda","doi":"10.1016/j.suscom.2024.100991","DOIUrl":null,"url":null,"abstract":"<div><p>Massive multi-input multi-output (MIMO) is realized as the principal technology in the emerging fifth generation communication network system. Hybrid structure uplink communication is considered for the MIMO Non-orthogonal multiple access (MIMO-NOMA) system’s beam forming and power efficiency improvement through the novel three-layer user grouping. In the three-layer user grouping, the K-means algorithm is adopted in the initial layer for grouping users among different clusters and rectifying clustering errors in the third layer. The second layer used the agglomerative nesting (AGNES) algorithm for merging smaller clusters based on the channel correlation and angles of arrival similarity. The beam selection is carried out to minimize the intrusion of defined beam elements and to overcome beam overlapping problems. The non-convex optimization of the power allocating problem is modified as a convex problem by introducing a Quadratic transform (QT) to minimize each user’s data rate requirement. The algorithm of coati optimization is proposed to iteratively optimize the power allocation problem. The simulation results show that our proposed methodology goes beyond the existing schemes in terms of energy efficiency beyond the maximum power and achievable sum rate can be achieved.</p></div>","PeriodicalId":48686,"journal":{"name":"Sustainable Computing-Informatics & Systems","volume":"43 ","pages":"Article 100991"},"PeriodicalIF":3.8000,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Energy efficiency enhancement in millimetre-wave MIMO-NOMA using three layer user grouping and adaptive power allocation algorithm\",\"authors\":\"K. Ramesh Chandra ,&nbsp;Somasekhar Borugadda\",\"doi\":\"10.1016/j.suscom.2024.100991\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Massive multi-input multi-output (MIMO) is realized as the principal technology in the emerging fifth generation communication network system. Hybrid structure uplink communication is considered for the MIMO Non-orthogonal multiple access (MIMO-NOMA) system’s beam forming and power efficiency improvement through the novel three-layer user grouping. In the three-layer user grouping, the K-means algorithm is adopted in the initial layer for grouping users among different clusters and rectifying clustering errors in the third layer. The second layer used the agglomerative nesting (AGNES) algorithm for merging smaller clusters based on the channel correlation and angles of arrival similarity. The beam selection is carried out to minimize the intrusion of defined beam elements and to overcome beam overlapping problems. The non-convex optimization of the power allocating problem is modified as a convex problem by introducing a Quadratic transform (QT) to minimize each user’s data rate requirement. The algorithm of coati optimization is proposed to iteratively optimize the power allocation problem. The simulation results show that our proposed methodology goes beyond the existing schemes in terms of energy efficiency beyond the maximum power and achievable sum rate can be achieved.</p></div>\",\"PeriodicalId\":48686,\"journal\":{\"name\":\"Sustainable Computing-Informatics & Systems\",\"volume\":\"43 \",\"pages\":\"Article 100991\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2024-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sustainable Computing-Informatics & Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2210537924000362\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Computing-Informatics & Systems","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2210537924000362","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
引用次数: 0

摘要

大规模多输入多输出(MIMO)是新兴的第五代通信网络系统的主要技术。混合结构上行链路通信被认为是 MIMO 非正交多址(MIMO-NOMA)系统波束形成和功率效率改进的一种新的三层用户分组方式。在三层用户分组中,初始层采用 K-means 算法对不同簇之间的用户进行分组,并在第三层纠正分组错误。第二层采用聚类嵌套(AGNES)算法,根据信道相关性和到达角相似性合并较小的簇。波束选择是为了尽量减少已定义波束元素的侵入,并克服波束重叠问题。通过引入二次变换(QT),将功率分配问题的非凸优化修改为凸问题,以最小化每个用户的数据速率要求。我们提出了 coati 优化算法来迭代优化功率分配问题。仿真结果表明,我们提出的方法在能效方面超越了现有方案,可以达到最大功率和可实现的总和速率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Energy efficiency enhancement in millimetre-wave MIMO-NOMA using three layer user grouping and adaptive power allocation algorithm

Massive multi-input multi-output (MIMO) is realized as the principal technology in the emerging fifth generation communication network system. Hybrid structure uplink communication is considered for the MIMO Non-orthogonal multiple access (MIMO-NOMA) system’s beam forming and power efficiency improvement through the novel three-layer user grouping. In the three-layer user grouping, the K-means algorithm is adopted in the initial layer for grouping users among different clusters and rectifying clustering errors in the third layer. The second layer used the agglomerative nesting (AGNES) algorithm for merging smaller clusters based on the channel correlation and angles of arrival similarity. The beam selection is carried out to minimize the intrusion of defined beam elements and to overcome beam overlapping problems. The non-convex optimization of the power allocating problem is modified as a convex problem by introducing a Quadratic transform (QT) to minimize each user’s data rate requirement. The algorithm of coati optimization is proposed to iteratively optimize the power allocation problem. The simulation results show that our proposed methodology goes beyond the existing schemes in terms of energy efficiency beyond the maximum power and achievable sum rate can be achieved.

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
Sustainable Computing-Informatics & Systems
Sustainable Computing-Informatics & Systems COMPUTER SCIENCE, HARDWARE & ARCHITECTUREC-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
10.70
自引率
4.40%
发文量
142
期刊介绍: Sustainable computing is a rapidly expanding research area spanning the fields of computer science and engineering, electrical engineering as well as other engineering disciplines. The aim of Sustainable Computing: Informatics and Systems (SUSCOM) is to publish the myriad research findings related to energy-aware and thermal-aware management of computing resource. Equally important is a spectrum of related research issues such as applications of computing that can have ecological and societal impacts. SUSCOM publishes original and timely research papers and survey articles in current areas of power, energy, temperature, and environment related research areas of current importance to readers. SUSCOM has an editorial board comprising prominent researchers from around the world and selects competitively evaluated peer-reviewed papers.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信