A Case for Frequency Domain Window Based Nyquist Filter Design

Q. Chaudhari
{"title":"A Case for Frequency Domain Window Based Nyquist Filter Design","authors":"Q. Chaudhari","doi":"10.1109/ICSPCS.2018.8631761","DOIUrl":null,"url":null,"abstract":"In the digital domain, a Square-Root Raised Cosine Filter (SRRC) has historically been used in most of the wireless standards for shaping the spectrum at the Tx and matched filtering the signal at the Rx (the combination forms a Raised Cosine (RC) filter). However, the performance of an SRRC filter in terms of peak ISI and peak sidelobe attenuation is fairly average, to say the least. A transformed lowpass filter designed according to Parks-McClellan algorithm is an alternative pulse shaping technique which is generally believed to be optimal due to the lowpass filter coefficients being the optimal solution based on Remez exchange algorithm and Chebyshev approximation theory such that the maximum error between the desired and the actual frequency response is minimized. In this paper, we show that another technique proposed in [3] based on an optimized frequency domain window convolved with a rectangular spectrum matches fairly well against the lowpass filter based method at all instances in terms of peak ISI and sidelobe attenuation.","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSPCS.2018.8631761","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In the digital domain, a Square-Root Raised Cosine Filter (SRRC) has historically been used in most of the wireless standards for shaping the spectrum at the Tx and matched filtering the signal at the Rx (the combination forms a Raised Cosine (RC) filter). However, the performance of an SRRC filter in terms of peak ISI and peak sidelobe attenuation is fairly average, to say the least. A transformed lowpass filter designed according to Parks-McClellan algorithm is an alternative pulse shaping technique which is generally believed to be optimal due to the lowpass filter coefficients being the optimal solution based on Remez exchange algorithm and Chebyshev approximation theory such that the maximum error between the desired and the actual frequency response is minimized. In this paper, we show that another technique proposed in [3] based on an optimized frequency domain window convolved with a rectangular spectrum matches fairly well against the lowpass filter based method at all instances in terms of peak ISI and sidelobe attenuation.
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
基于频域窗的奈奎斯特滤波器设计实例
在数字领域,平方根上升余弦滤波器(SRRC)历来用于大多数无线标准中,用于在Tx处塑造频谱并在Rx处匹配滤波信号(组合形成上升余弦滤波器(RC))。然而,在峰值ISI和峰值旁瓣衰减方面,SRRC滤波器的性能至少可以说是相当平均的。根据Parks-McClellan算法设计的变换低通滤波器是一种替代脉冲整形技术,由于低通滤波器系数是基于Remez交换算法和Chebyshev近似理论的最优解,使得期望频率响应与实际频率响应之间的最大误差最小,因此通常被认为是最优的。在本文中,我们证明了[3]中提出的另一种基于优化的频域窗口与矩形频谱卷积的技术在峰值ISI和旁瓣衰减方面与基于低通滤波器的方法在所有实例中都相当匹配。
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
Design, Implementation & Performance Analysis of Low Cost High Performance Computing (HPC) Clusters Range Extension Using Opal in Open Environments The Smallest Critical Sets of Latin Squares Forward-Looking Clutter Suppression Approach of Airborne Radar Based on KA-JDL Algorithm of Object Filtering Analysis of Variance of Opinion Scores for MPEG-4 Scalable and Advanced Video Coding
×
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