2.86Gb/s全灵活MU-MIMO处理器,用于共同优化28nm CMOS技术的用户选择、功率分配和预编码

Seungsik Moon, N. Lee, Youngjoo Lee
{"title":"2.86Gb/s全灵活MU-MIMO处理器,用于共同优化28nm CMOS技术的用户选择、功率分配和预编码","authors":"Seungsik Moon, N. Lee, Youngjoo Lee","doi":"10.1109/CICC53496.2022.9772835","DOIUrl":null,"url":null,"abstract":"In 5G networks, as growing data usage exponentially, mobile operators need to increase network capacity. To increase the spectral efficiency of massive multiple-input multiple-output (MIMO) system, it is essential to enlarge the number of co-scheduled user equipments (UEs). As increasing the number of co-scheduled UEs up to the number of base station (BS) antennas, the conventional linear precoding schemes such as zero-forcing and maximum ratio transmission show poor capacity, as shown in Fig. 1. As a result, joint user selection, power allocation, and beamforming schemes, including the rank-adaptation zero-forcing (RA-ZF) and generalized power iteration precoding (GPIP) algorithms, are proposed for large-scale massive MIMO systems. However, the prior works on massive MIMO baseband architectures [1]–[4] are no longer suitable for these advanced algorithms; because they do not consider user selection or power allocation. Consequently, it is crucial to develop energy-and computationally efficient BS architecture that realizes the advanced algorithms to achieve a high spectral efficiency gain.","PeriodicalId":415990,"journal":{"name":"2022 IEEE Custom Integrated Circuits Conference (CICC)","volume":"160 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A 2.86Gb/s Fully-Flexible MU-MIMO Processor for Jointly Optimizing User Selection, Power Allocation, and Precoding in 28nm CMOS Technology\",\"authors\":\"Seungsik Moon, N. Lee, Youngjoo Lee\",\"doi\":\"10.1109/CICC53496.2022.9772835\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In 5G networks, as growing data usage exponentially, mobile operators need to increase network capacity. To increase the spectral efficiency of massive multiple-input multiple-output (MIMO) system, it is essential to enlarge the number of co-scheduled user equipments (UEs). As increasing the number of co-scheduled UEs up to the number of base station (BS) antennas, the conventional linear precoding schemes such as zero-forcing and maximum ratio transmission show poor capacity, as shown in Fig. 1. As a result, joint user selection, power allocation, and beamforming schemes, including the rank-adaptation zero-forcing (RA-ZF) and generalized power iteration precoding (GPIP) algorithms, are proposed for large-scale massive MIMO systems. However, the prior works on massive MIMO baseband architectures [1]–[4] are no longer suitable for these advanced algorithms; because they do not consider user selection or power allocation. Consequently, it is crucial to develop energy-and computationally efficient BS architecture that realizes the advanced algorithms to achieve a high spectral efficiency gain.\",\"PeriodicalId\":415990,\"journal\":{\"name\":\"2022 IEEE Custom Integrated Circuits Conference (CICC)\",\"volume\":\"160 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE Custom Integrated Circuits Conference (CICC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CICC53496.2022.9772835\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Custom Integrated Circuits Conference (CICC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CICC53496.2022.9772835","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5G网络中,随着数据使用量呈指数级增长,移动运营商需要增加网络容量。为了提高大规模多输入多输出(MIMO)系统的频谱效率,必须增加共调度用户设备的数量。当共调度终端数量增加到基站(BS)天线数量时,强制为零和最大比传输等传统线性预编码方案的容量较差,如图1所示。因此,针对大规模MIMO系统,提出了联合用户选择、功率分配和波束形成方案,包括秩自适应零强制(RA-ZF)和广义功率迭代预编码(gip)算法。然而,先前关于大规模MIMO基带架构的工作[1]-[4]不再适合这些高级算法;因为它们不考虑用户选择或权力分配。因此,开发能源和计算效率高的BS架构,实现先进的算法,以实现高频谱效率增益是至关重要的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A 2.86Gb/s Fully-Flexible MU-MIMO Processor for Jointly Optimizing User Selection, Power Allocation, and Precoding in 28nm CMOS Technology
In 5G networks, as growing data usage exponentially, mobile operators need to increase network capacity. To increase the spectral efficiency of massive multiple-input multiple-output (MIMO) system, it is essential to enlarge the number of co-scheduled user equipments (UEs). As increasing the number of co-scheduled UEs up to the number of base station (BS) antennas, the conventional linear precoding schemes such as zero-forcing and maximum ratio transmission show poor capacity, as shown in Fig. 1. As a result, joint user selection, power allocation, and beamforming schemes, including the rank-adaptation zero-forcing (RA-ZF) and generalized power iteration precoding (GPIP) algorithms, are proposed for large-scale massive MIMO systems. However, the prior works on massive MIMO baseband architectures [1]–[4] are no longer suitable for these advanced algorithms; because they do not consider user selection or power allocation. Consequently, it is crucial to develop energy-and computationally efficient BS architecture that realizes the advanced algorithms to achieve a high spectral efficiency gain.
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
×
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