Transmit Beamforming Design for ISAC With Stacked Intelligent Metasurfaces

IF 7.5 2区 计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Transactions on Vehicular Technology Pub Date : 2024-12-16 DOI:10.1109/TVT.2024.3517709
Shunyu Li;Fan Zhang;Tianqi Mao;Rui Na;Zhaocheng Wang;George K. Karagiannidis
{"title":"Transmit Beamforming Design for ISAC With Stacked Intelligent Metasurfaces","authors":"Shunyu Li;Fan Zhang;Tianqi Mao;Rui Na;Zhaocheng Wang;George K. Karagiannidis","doi":"10.1109/TVT.2024.3517709","DOIUrl":null,"url":null,"abstract":"This paper proposes a transmit beamforming strategy for the integrated sensing and communication (ISAC) systems enabled by the novel stacked intelligent metasurface (SIM) architecture, different from conventional single-layer reconfigurable intelligent surface (RIS) by cascading multiple transmissive metasurface layers, where the base station (BS) simultaneously performs downlink communication and radar target detection via fully passive wave domain beamforming, result in the significant reduction in hardware cost and power consumption. To ensure superior dual-function performance simultaneously, we design the multi-layer cascading beamformer by maximizing the sum rate of the users while optimally shaping the normalized beam pattern for detection. A dual-normalized differential gradient descent (<inline-formula><tex-math>$\\text{D}^{3}$</tex-math></inline-formula>) algorithm is further proposed to solve the resulting non-convex multi-objective problem (MOP), where gradient differences and dual normalization are employed to ensure a flexible trade-off between communication and sensing objectives at the gradient level, providing finer control over the optimization process. Numerical results demonstrate the superiority of the proposed beamforming design in terms of balancing communication and sensing performance.","PeriodicalId":13421,"journal":{"name":"IEEE Transactions on Vehicular Technology","volume":"74 4","pages":"6767-6772"},"PeriodicalIF":7.5000,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Vehicular Technology","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10803090/","RegionNum":2,"RegionCategory":"计算机科学","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

This paper proposes a transmit beamforming strategy for the integrated sensing and communication (ISAC) systems enabled by the novel stacked intelligent metasurface (SIM) architecture, different from conventional single-layer reconfigurable intelligent surface (RIS) by cascading multiple transmissive metasurface layers, where the base station (BS) simultaneously performs downlink communication and radar target detection via fully passive wave domain beamforming, result in the significant reduction in hardware cost and power consumption. To ensure superior dual-function performance simultaneously, we design the multi-layer cascading beamformer by maximizing the sum rate of the users while optimally shaping the normalized beam pattern for detection. A dual-normalized differential gradient descent ($\text{D}^{3}$) algorithm is further proposed to solve the resulting non-convex multi-objective problem (MOP), where gradient differences and dual normalization are employed to ensure a flexible trade-off between communication and sensing objectives at the gradient level, providing finer control over the optimization process. Numerical results demonstrate the superiority of the proposed beamforming design in terms of balancing communication and sensing performance.
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
采用堆叠智能元面的 ISAC 发射波束成形设计
本文提出了一种基于新型堆叠智能元表面(SIM)架构的集成传感与通信(ISAC)系统的发射波束形成策略,该策略不同于传统的单层可重构智能表面(RIS),通过级联多个发射元表面层,基站(BS)通过完全无源波束形成波域同时进行下行通信和雷达目标探测。显著降低硬件成本和功耗。为了同时保证优越的双功能性能,我们通过最大化用户的和速率来设计多层级联波束形成器,同时优化形成用于检测的归一化波束模式。进一步提出了一种双归一化微分梯度下降($\text{D}^{3}$)算法来解决由此产生的非凸多目标问题(MOP),其中使用梯度差分和对偶归一化来确保在梯度级别上通信和感知目标之间的灵活权衡,从而对优化过程提供更精细的控制。数值结果表明了所提出的波束形成设计在平衡通信性能和传感性能方面的优越性。
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
CiteScore
6.00
自引率
8.80%
发文量
1245
审稿时长
6.3 months
期刊介绍: The scope of the Transactions is threefold (which was approved by the IEEE Periodicals Committee in 1967) and is published on the journal website as follows: Communications: The use of mobile radio on land, sea, and air, including cellular radio, two-way radio, and one-way radio, with applications to dispatch and control vehicles, mobile radiotelephone, radio paging, and status monitoring and reporting. Related areas include spectrum usage, component radio equipment such as cavities and antennas, compute control for radio systems, digital modulation and transmission techniques, mobile radio circuit design, radio propagation for vehicular communications, effects of ignition noise and radio frequency interference, and consideration of the vehicle as part of the radio operating environment. Transportation Systems: The use of electronic technology for the control of ground transportation systems including, but not limited to, traffic aid systems; traffic control systems; automatic vehicle identification, location, and monitoring systems; automated transport systems, with single and multiple vehicle control; and moving walkways or people-movers. Vehicular Electronics: The use of electronic or electrical components and systems for control, propulsion, or auxiliary functions, including but not limited to, electronic controls for engineer, drive train, convenience, safety, and other vehicle systems; sensors, actuators, and microprocessors for onboard use; electronic fuel control systems; vehicle electrical components and systems collision avoidance systems; electromagnetic compatibility in the vehicle environment; and electric vehicles and controls.
期刊最新文献
Deep Reinforcement Learning-Enhanced Overlapping Coalition Formation with Blockchain-Secured Trust Management for Multi-UAV Networks MADRL-Driven Dynamic Coverage Center Adaptation for Multi-Beam Satellite System Terahertz Coverage Analysis with Fixed-Wing UAVs: Analytical Framework and Closed-Form Outage Modeling An Efficient Resource Allocation and Multicast Routing Strategy for IAB Networks With Hybrid Multicast/Unicast Traffic Sub-array Selection Optimization for Joint Self-Interference and Multi-User Interference Suppression in FD mMIMO
×
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学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
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