Power allocation strategies for 6G communication in VL-NOMA systems: an overview

IF 2.4 Q2 MULTIDISCIPLINARY SCIENCES Smart Science Pub Date : 2023-07-03 DOI:10.1080/23080477.2023.2225944
C. E. Ngene, P. Thakur, G. Singh, Prabhat Thakur E. Ngene, O. P. Thakur
{"title":"Power allocation strategies for 6G communication in VL-NOMA systems: an overview","authors":"C. E. Ngene, P. Thakur, G. Singh, Prabhat Thakur E. Ngene, O. P. Thakur","doi":"10.1080/23080477.2023.2225944","DOIUrl":null,"url":null,"abstract":"ABSTRACT This paper discusses an overview of power allocation (PA) strategy for enabled sixth-generation (6 G) communication in visible light non-orthogonal multiple access (VL-NOMA) scenario. Light emitting diode (LED) deployed in the advancement of VL-NOMA 6 G limit-less efficiencies when complemented with radio frequency (RF)/millimeter-wave ( ), terahertz (THz), free-space optical (FSO) and VL. The encountered challenges in the currently deployed fifth generation (5 G) technology such as signal failures, low power, data loss, latency from (5 ), and loss of signal strength were solved with 6 G providing disruptive technologies, latency from ( ), massive connectivity, cell-less communications, modified machine learning algorithms, new security measures, more energy-efficient, infrastructure smart networking management, new spectrum, artificial intelligence (AI), disaggregation and virtualization supporting enough bandwidth, and increase data rate. The PA uses available power to distribute entire signals assigning power levels to multi-devices connected to VL-NOMA applications for envisioned virtual reality, unlocking all the possibilities of an indoor and outdoor transmission positioned to achieve superior accuracy, reliability and unlimited access. The 6 G 2030 roadmap positioning LED as a carrier assigning VL-NOMA PA techniques for a green solution improving high quality of services, higher data rate, reduced power consumption (using metasurface schemes), high capacity, energy efficiencies, low cost, illumination, communication and indication as detailed herein. Graphical abstract","PeriodicalId":53436,"journal":{"name":"Smart Science","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Smart Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23080477.2023.2225944","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 1

Abstract

ABSTRACT This paper discusses an overview of power allocation (PA) strategy for enabled sixth-generation (6 G) communication in visible light non-orthogonal multiple access (VL-NOMA) scenario. Light emitting diode (LED) deployed in the advancement of VL-NOMA 6 G limit-less efficiencies when complemented with radio frequency (RF)/millimeter-wave ( ), terahertz (THz), free-space optical (FSO) and VL. The encountered challenges in the currently deployed fifth generation (5 G) technology such as signal failures, low power, data loss, latency from (5 ), and loss of signal strength were solved with 6 G providing disruptive technologies, latency from ( ), massive connectivity, cell-less communications, modified machine learning algorithms, new security measures, more energy-efficient, infrastructure smart networking management, new spectrum, artificial intelligence (AI), disaggregation and virtualization supporting enough bandwidth, and increase data rate. The PA uses available power to distribute entire signals assigning power levels to multi-devices connected to VL-NOMA applications for envisioned virtual reality, unlocking all the possibilities of an indoor and outdoor transmission positioned to achieve superior accuracy, reliability and unlimited access. The 6 G 2030 roadmap positioning LED as a carrier assigning VL-NOMA PA techniques for a green solution improving high quality of services, higher data rate, reduced power consumption (using metasurface schemes), high capacity, energy efficiencies, low cost, illumination, communication and indication as detailed herein. Graphical abstract
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
VL-NOMA系统中6G通信的功率分配策略综述
摘要本文讨论了启用的第六代(6 G) 可见光非正交多址(VL-NOMA)场景中的通信。在VL-NOMA 6的发展中部署的发光二极管 当与射频(RF)/毫米波()、太赫兹(THz)、自由空间光学(FSO)和VL互补时,G限制了较低的效率。目前部署的第五代(5 G) 诸如信号故障、低功率、数据丢失、来自(5)的延迟和信号强度损失等技术都用6来解决 G提供颠覆性技术、来自()的延迟、大规模连接、无蜂窝通信、改进的机器学习算法、新的安全措施、更节能的基础设施智能网络管理、新频谱、人工智能(AI)、支持足够带宽的分解和虚拟化,并提高数据速率。PA使用可用功率将整个信号分配给连接到VL-NOMA应用程序的多个设备,用于设想的虚拟现实,解锁室内和室外传输的所有可能性,以实现卓越的准确性、可靠性和无限制的访问。6 G 2030路线图将LED定位为载波,为绿色解决方案分配VL-NOMA PA技术,如本文所述,该技术改善了高服务质量、更高的数据速率、降低的功耗(使用元表面方案)、高容量、能效、低成本、照明、通信和指示。图形摘要
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
Smart Science
Smart Science Engineering-Engineering (all)
CiteScore
4.70
自引率
4.30%
发文量
21
期刊介绍: Smart Science (ISSN 2308-0477) is an international, peer-reviewed journal that publishes significant original scientific researches, and reviews and analyses of current research and science policy. We welcome submissions of high quality papers from all fields of science and from any source. Articles of an interdisciplinary nature are particularly welcomed. Smart Science aims to be among the top multidisciplinary journals covering a broad spectrum of smart topics in the fields of materials science, chemistry, physics, engineering, medicine, and biology. Smart Science is currently focusing on the topics of Smart Manufacturing (CPS, IoT and AI) for Industry 4.0, Smart Energy and Smart Chemistry and Materials. Other specific research areas covered by the journal include, but are not limited to: 1. Smart Science in the Future 2. Smart Manufacturing: -Cyber-Physical System (CPS) -Internet of Things (IoT) and Internet of Brain (IoB) -Artificial Intelligence -Smart Computing -Smart Design/Machine -Smart Sensing -Smart Information and Networks 3. Smart Energy and Thermal/Fluidic Science 4. Smart Chemistry and Materials
期刊最新文献
A comprehensive review on stochastic modeling of electric vehicle charging load demand regarding various uncertainties Sentiment analysis technique on product reviews using Inception Recurrent Convolutional Neural Network with ResNet Transfer Learning Reinforced black widow algorithm with restoration technique based on optimized deep generative adversarial network Multi-headed U-Net: an automated nuclei segmentation technique using Tikhonov filter-based unsharp masking Islanded micro-grid under variable load conditions for local distribution network using artificial neural network
×
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