SVD-Aided, Iteratively Detected Spatial Division Multiplexing Using Long-Range Channel Prediction

A. Ahrens, W. Liu, S. Ng, V. Kühn, Lie-liang Yang, L. Hanzo
{"title":"SVD-Aided, Iteratively Detected Spatial Division Multiplexing Using Long-Range Channel Prediction","authors":"A. Ahrens, W. Liu, S. Ng, V. Kühn, Lie-liang Yang, L. Hanzo","doi":"10.1109/SIPS.2007.4387579","DOIUrl":null,"url":null,"abstract":"In this contribution iteratively detected spatial division multiplexing is investigated under the constraint of a fixed data throughput. Existing bit loading and transmit power allocation techniques are often optimized for maintaining both a fixed transmit power and a fixed target bit-error rate, while attempting to maximize the overall data-rate, albeit delay-critical real-time interactive applications, such as voice or video transmission, may require a fixed data rate. As an alternative design option, in addition to sophisticated joint bit- and power loading, in this contribution we invoke both coded modulation as well as channel prediction and identify the most beneficial number of modulation signalling levels, while minimizing the bit-error ratio under the constraints of a given fixed throughput. Our performance results show the superiority of bit-interleaved coded modulation using iterative decoding (BICM-ID) against turbo trellis-coded modulation (TTCM), regardless of using idealistic perfect or realistic imperfect channel state information (CSI).","PeriodicalId":93225,"journal":{"name":"Proceedings. IEEE Workshop on Signal Processing Systems (2007-2014)","volume":"1 1","pages":"391-396"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. IEEE Workshop on Signal Processing Systems (2007-2014)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIPS.2007.4387579","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

In this contribution iteratively detected spatial division multiplexing is investigated under the constraint of a fixed data throughput. Existing bit loading and transmit power allocation techniques are often optimized for maintaining both a fixed transmit power and a fixed target bit-error rate, while attempting to maximize the overall data-rate, albeit delay-critical real-time interactive applications, such as voice or video transmission, may require a fixed data rate. As an alternative design option, in addition to sophisticated joint bit- and power loading, in this contribution we invoke both coded modulation as well as channel prediction and identify the most beneficial number of modulation signalling levels, while minimizing the bit-error ratio under the constraints of a given fixed throughput. Our performance results show the superiority of bit-interleaved coded modulation using iterative decoding (BICM-ID) against turbo trellis-coded modulation (TTCM), regardless of using idealistic perfect or realistic imperfect channel state information (CSI).
基于svd辅助的远程信道预测迭代检测空分复用
在此贡献中,研究了在固定数据吞吐量约束下迭代检测的空分复用。现有的位加载和传输功率分配技术通常针对保持固定的传输功率和固定的目标误码率进行了优化,同时试图最大化总体数据速率,尽管延迟关键型实时交互应用(如语音或视频传输)可能需要固定的数据速率。作为另一种设计选择,除了复杂的联合比特和功率负载外,在本贡献中,我们调用编码调制和信道预测,并确定最有利的调制信号电平数量,同时在给定固定吞吐量的约束下最大限度地降低误码率。我们的性能结果表明,无论使用理想的完美信道状态信息(CSI)还是现实的不完美信道状态信息(CSI),使用迭代解码(BICM-ID)的位交错编码调制(bcm - id)都优于turbo栅格编码调制(TTCM)。
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 求助全文
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