Performance Analysis of Sparse Code Multiple Access Transceiver System for Massive Machine - Type Communication

S. Shruthi, K. Saraswathi
{"title":"Performance Analysis of Sparse Code Multiple Access Transceiver System for Massive Machine - Type Communication","authors":"S. Shruthi, K. Saraswathi","doi":"10.1109/GCAT55367.2022.9971840","DOIUrl":null,"url":null,"abstract":"The Sparse Code Multiple Access (SCMA) is one of the code-domain non-orthogonal multiple access schemes (CD-NOMA) employed in wireless communication systems. The SCMA is a multi-dimensional codebook based spreading procedure where the incoming bits of several users are mapped directly to multi-dimensional code words that are selected from sparse codebooks. The SCMA increases the spectral efficiency by allowing a large number of users to share the time and frequency resources which improves overall system performance. This has gained attention in the field of massive-machine type communication (mMtc) in 5G to satisfy huge demand on massive connectivity and data traffic. In this paper, the design and simulation of the SCMA system for the uplink scenario is carried out for 6 and 8 UEs. The Turbo coder is used for forward error correction and the Log-message passing algorithm (Log-MPA) is used as a detection scheme. The performance analysis of SCMA system is carrier out using block error rate (BLER) for 6 and 8 UEs.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GCAT55367.2022.9971840","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

The Sparse Code Multiple Access (SCMA) is one of the code-domain non-orthogonal multiple access schemes (CD-NOMA) employed in wireless communication systems. The SCMA is a multi-dimensional codebook based spreading procedure where the incoming bits of several users are mapped directly to multi-dimensional code words that are selected from sparse codebooks. The SCMA increases the spectral efficiency by allowing a large number of users to share the time and frequency resources which improves overall system performance. This has gained attention in the field of massive-machine type communication (mMtc) in 5G to satisfy huge demand on massive connectivity and data traffic. In this paper, the design and simulation of the SCMA system for the uplink scenario is carried out for 6 and 8 UEs. The Turbo coder is used for forward error correction and the Log-message passing algorithm (Log-MPA) is used as a detection scheme. The performance analysis of SCMA system is carrier out using block error rate (BLER) for 6 and 8 UEs.
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
大规模机型通信稀疏码多址收发系统性能分析
稀疏码多址(SCMA)是一种用于无线通信系统的码域非正交多址(CD-NOMA)方案。SCMA是一种基于多维码本的扩展过程,它将多个用户的输入比特直接映射到从稀疏码本中选择的多维码字上。SCMA通过允许大量用户共享时间和频率资源来提高频谱效率,从而提高系统的整体性能。这在5G的大机器通信(mMtc)领域受到了关注,以满足对海量连接和数据流量的巨大需求。本文对上行场景下的SCMA系统进行了6台和8台终端的设计和仿真。采用Turbo码进行前向纠错,采用日志消息传递算法(Log-message passing algorithm, Log-MPA)作为检测方案。采用分组误码率(BLER)对SCMA系统进行了6和8个ue的性能分析。
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
Investigating the role of Named Entity Recognition in Question Answering Models Neural Machine Translation for English-Assamese Language Pair using Transformer Cascading Neural Network with Particle Swarm Optimization Combination of APF and SVC for the Power Quality Improvement in Microgrid Distracted Driver Posture Recognition
×
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