Multipath Component Power Delay Profile Based Ranging

IF 8.7 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Journal of Selected Topics in Signal Processing Pub Date : 2024-11-04 DOI:10.1109/JSTSP.2024.3491580
Fangqing Xiao;Zilu Zhao;Dirk T. M. Slock
{"title":"Multipath Component Power Delay Profile Based Ranging","authors":"Fangqing Xiao;Zilu Zhao;Dirk T. M. Slock","doi":"10.1109/JSTSP.2024.3491580","DOIUrl":null,"url":null,"abstract":"Precision ranging technology has become indispensable for ensuring efficient, reliable, and low-latency fifth-generation (5G) networks. In this paper, we propose a novel ranging method which is multipath component (MPC) power delay profile (PDP) based ranging. Whereas the Received Signal Strength (RSS) only summarizes the PDP into a single characteristic, we aim to furthermore exploit the range dependent curvature of the PDP envelope over its delay spread. However, the multipath propagation only allows to sample the PDP envelope at the path delays and suffers from (slow) fading. Hence our approach involves constructing a statistical fading model of the PDP and establishing a relationship between the distribution parameters and the propagation distance. To theoretically validate the feasibility of our proposed method, we adopt the widely accepted Nakagami-m fading model, which renders traditional estimation methods difficult to apply. Therefore we introduce the Expectation Maximization (EM)-Revisited Vector Approximate Message Passing (ReVAMP) algorithm. This algorithm is specifically designed to handle difficulties in parameter estimation for Gaussian linear models (GLMs) with hidden random variables and intractable posterior distributions. Extensive numerical simulation results have been conducted which exhibit preliminary evidence of the effectiveness of our MPCPDP-based ranging method compared to the received signal strength (RSS)-based method. Moreover, the versatility of the EM-ReVAMP algorithm allows for its extension to other statistical fading models beyond the Nakagami-m model with minor modifications, which opens the door to potential improvements based on more accurate statistical fading models. Nevertheless, the applicability of our MPCPDP-based ranging method should be validated in real-world scenarios in future studies.","PeriodicalId":13038,"journal":{"name":"IEEE Journal of Selected Topics in Signal Processing","volume":"18 5","pages":"950-963"},"PeriodicalIF":8.7000,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Selected Topics in Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10742342/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

Abstract

Precision ranging technology has become indispensable for ensuring efficient, reliable, and low-latency fifth-generation (5G) networks. In this paper, we propose a novel ranging method which is multipath component (MPC) power delay profile (PDP) based ranging. Whereas the Received Signal Strength (RSS) only summarizes the PDP into a single characteristic, we aim to furthermore exploit the range dependent curvature of the PDP envelope over its delay spread. However, the multipath propagation only allows to sample the PDP envelope at the path delays and suffers from (slow) fading. Hence our approach involves constructing a statistical fading model of the PDP and establishing a relationship between the distribution parameters and the propagation distance. To theoretically validate the feasibility of our proposed method, we adopt the widely accepted Nakagami-m fading model, which renders traditional estimation methods difficult to apply. Therefore we introduce the Expectation Maximization (EM)-Revisited Vector Approximate Message Passing (ReVAMP) algorithm. This algorithm is specifically designed to handle difficulties in parameter estimation for Gaussian linear models (GLMs) with hidden random variables and intractable posterior distributions. Extensive numerical simulation results have been conducted which exhibit preliminary evidence of the effectiveness of our MPCPDP-based ranging method compared to the received signal strength (RSS)-based method. Moreover, the versatility of the EM-ReVAMP algorithm allows for its extension to other statistical fading models beyond the Nakagami-m model with minor modifications, which opens the door to potential improvements based on more accurate statistical fading models. Nevertheless, the applicability of our MPCPDP-based ranging method should be validated in real-world scenarios in future studies.
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
基于多径分量功率延迟曲线的测距
精确测距技术已成为确保高效、可靠和低延迟的第五代(5G)网络不可或缺的技术。本文提出了一种基于多径分量(MPC)功率延迟曲线(PDP)的测距方法。鉴于接收信号强度(RSS)仅将PDP总结为单个特征,我们的目标是进一步利用PDP包络在其延迟扩展上的范围相关曲率。然而,多径传播只允许在路径延迟时对PDP包络进行采样,并且受到(缓慢)衰落的影响。因此,我们的方法包括建立PDP的统计衰落模型,并建立分布参数与传播距离之间的关系。为了从理论上验证我们提出的方法的可行性,我们采用了被广泛接受的Nakagami-m衰落模型,这使得传统的估计方法难以应用。因此,我们引入了期望最大化(EM)-重访向量近似消息传递(ReVAMP)算法。该算法是专门针对具有隐藏随机变量和难以处理的后验分布的高斯线性模型的参数估计问题而设计的。大量的数值模拟结果显示,与基于接收信号强度(RSS)的方法相比,基于mpcpdp的测距方法具有初步的有效性。此外,EM-ReVAMP算法的通用性允许将其扩展到Nakagami-m模型之外的其他统计衰落模型,只需进行少量修改,这为基于更精确的统计衰落模型的潜在改进打开了大门。然而,在未来的研究中,我们基于mpcpdp的测距方法的适用性应该在现实场景中得到验证。
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
IEEE Journal of Selected Topics in Signal Processing
IEEE Journal of Selected Topics in Signal Processing 工程技术-工程:电子与电气
CiteScore
19.00
自引率
1.30%
发文量
135
审稿时长
3 months
期刊介绍: The IEEE Journal of Selected Topics in Signal Processing (JSTSP) focuses on the Field of Interest of the IEEE Signal Processing Society, which encompasses the theory and application of various signal processing techniques. These techniques include filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals using digital or analog devices. The term "signal" covers a wide range of data types, including audio, video, speech, image, communication, geophysical, sonar, radar, medical, musical, and others. The journal format allows for in-depth exploration of signal processing topics, enabling the Society to cover both established and emerging areas. This includes interdisciplinary fields such as biomedical engineering and language processing, as well as areas not traditionally associated with engineering.
期刊最新文献
Front Cover Table of Contents IEEE Signal Processing Society Information List of Reviewers 2024 Editorial JSTSP NSAC Editorial
×
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