基于人工智能的水声通道均衡器设计

Fatma Ceren Yücel, Meryem Maras, Talat Kepezkaya, Elif Nur Ayvaz, A. Özen
{"title":"基于人工智能的水声通道均衡器设计","authors":"Fatma Ceren Yücel, Meryem Maras, Talat Kepezkaya, Elif Nur Ayvaz, A. Özen","doi":"10.1109/SIU55565.2022.9864992","DOIUrl":null,"url":null,"abstract":"In this study, it is suggested to use artificial intelligence assisted fuzzy logic based LMS (F-LMS) algorithm to improve the performance of single carrier (SC) underwater acoustic communication (UWAC) systems in multipath underwater acoustic channel environments. Numerical simulation studies are carried out to compare the proposed F-LMS algorithm with the bit error rate (BER) and mean square error (MSE) performance measures over decision feedback equalizer (DFE) and channel matched filter DFE (CMF-DFE). From the produced numerical results, it is understood that the best gains are achieved in both MSE and BER simulations with the proposed F-LMS algorithm. In addition to these, the most important contribution of the proposed study is to eliminate the error floor that occurs in DFE equalizers in BER simulations with CMF-DFE equalizers.","PeriodicalId":115446,"journal":{"name":"2022 30th Signal Processing and Communications Applications Conference (SIU)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial Intelligence Based Under Water Acoustic Channel Equalizer Design\",\"authors\":\"Fatma Ceren Yücel, Meryem Maras, Talat Kepezkaya, Elif Nur Ayvaz, A. Özen\",\"doi\":\"10.1109/SIU55565.2022.9864992\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study, it is suggested to use artificial intelligence assisted fuzzy logic based LMS (F-LMS) algorithm to improve the performance of single carrier (SC) underwater acoustic communication (UWAC) systems in multipath underwater acoustic channel environments. Numerical simulation studies are carried out to compare the proposed F-LMS algorithm with the bit error rate (BER) and mean square error (MSE) performance measures over decision feedback equalizer (DFE) and channel matched filter DFE (CMF-DFE). From the produced numerical results, it is understood that the best gains are achieved in both MSE and BER simulations with the proposed F-LMS algorithm. In addition to these, the most important contribution of the proposed study is to eliminate the error floor that occurs in DFE equalizers in BER simulations with CMF-DFE equalizers.\",\"PeriodicalId\":115446,\"journal\":{\"name\":\"2022 30th Signal Processing and Communications Applications Conference (SIU)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 30th Signal Processing and Communications Applications Conference (SIU)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIU55565.2022.9864992\",\"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 30th Signal Processing and Communications Applications Conference (SIU)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIU55565.2022.9864992","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本研究提出利用人工智能辅助的基于模糊逻辑的LMS (F-LMS)算法提高单载波水声通信(UWAC)系统在多径水声信道环境下的性能。通过数值仿真研究,比较了所提出的F-LMS算法与决策反馈均衡器(DFE)和信道匹配滤波器(CMF-DFE)的误码率(BER)和均方误差(MSE)性能。从所产生的数值结果中可以理解,使用所提出的F-LMS算法在MSE和BER模拟中都获得了最佳增益。除此之外,本研究最重要的贡献是消除了使用CMF-DFE均衡器进行误码率模拟时DFE均衡器中出现的误差层。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Artificial Intelligence Based Under Water Acoustic Channel Equalizer Design
In this study, it is suggested to use artificial intelligence assisted fuzzy logic based LMS (F-LMS) algorithm to improve the performance of single carrier (SC) underwater acoustic communication (UWAC) systems in multipath underwater acoustic channel environments. Numerical simulation studies are carried out to compare the proposed F-LMS algorithm with the bit error rate (BER) and mean square error (MSE) performance measures over decision feedback equalizer (DFE) and channel matched filter DFE (CMF-DFE). From the produced numerical results, it is understood that the best gains are achieved in both MSE and BER simulations with the proposed F-LMS algorithm. In addition to these, the most important contribution of the proposed study is to eliminate the error floor that occurs in DFE equalizers in BER simulations with CMF-DFE equalizers.
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
期刊最新文献
Traffic Prediction with Peak-Aware Temporal Graph Convolutional Networks Artificial Neural Network Based Fault Diagnostic System for Wind Turbines Remaining Useful Life Prediction on C-MAPSS Dataset via Joint Autoencoder-Regression Architecture A New Fast Walsh Hadamard Transform Spread UW-Optical-OFDM Waveform Indoor Localization with Transfer Learning
×
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