Enhanced ISAC Framework for Moving Target Assisted by Beyond-Diagonal RIS: Accurate Localization and Efficient Communication

IF 7.9 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2025-03-19 DOI:10.1109/TNSE.2025.3571278

Dawei Wang;Zijun Wang;Weichao Yang;Hongbo Zhao;Yixin He;Li Li;Zhongxiang Wei;Fuhui Zhou

{"title":"Enhanced ISAC Framework for Moving Target Assisted by Beyond-Diagonal RIS: Accurate Localization and Efficient Communication","authors":"Dawei Wang;Zijun Wang;Weichao Yang;Hongbo Zhao;Yixin He;Li Li;Zhongxiang Wei;Fuhui Zhou","doi":"10.1109/TNSE.2025.3571278","DOIUrl":null,"url":null,"abstract":"This paper proposes an innovative Integrated Sensing and Communication (ISAC) framework for moving target detection by leveraging beyond-diagonal RIS (BD-RIS) to improve beamforming performance and control wireless propagation. In this framework, we first design a novel target-tracking method for moving target detection based on Extended Kalman Filtering (EKF) with accurate cooperative localization. In addition, to further improve the sensing accuracy, we minimize the joint posterior Cramér-Rao bound (PCRB) for both target position and velocity constrained by the communication performance requirements, and maintain the orthogonality and symmetry constraints of BD-RIS. Given the non-convex nature of the problem, we break it into two subproblems, which are solved iteratively using the proposed alternating optimization (AO) algorithm. The AO algorithm incorporates a semidefinite relaxation (SDR) method for beamforming and a penalty dual decomposition (PDD) approach for BD-RIS optimization. The simulation results demonstrate that: (1) the proposed prediction method accurately tracks the position and velocity of the target in dynamic environments; (2) the proposed AO algorithm is efficient and effective, exhibiting fast convergence and achieving a performance improvement of 6.7<inline-formula><tex-math>$\\%$</tex-math></inline-formula> compared to conventional diagonal RIS.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 5","pages":"4299-4315"},"PeriodicalIF":7.9000,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Network Science and Engineering","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/11006508/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}

引用次数: 0

Abstract

This paper proposes an innovative Integrated Sensing and Communication (ISAC) framework for moving target detection by leveraging beyond-diagonal RIS (BD-RIS) to improve beamforming performance and control wireless propagation. In this framework, we first design a novel target-tracking method for moving target detection based on Extended Kalman Filtering (EKF) with accurate cooperative localization. In addition, to further improve the sensing accuracy, we minimize the joint posterior Cramér-Rao bound (PCRB) for both target position and velocity constrained by the communication performance requirements, and maintain the orthogonality and symmetry constraints of BD-RIS. Given the non-convex nature of the problem, we break it into two subproblems, which are solved iteratively using the proposed alternating optimization (AO) algorithm. The AO algorithm incorporates a semidefinite relaxation (SDR) method for beamforming and a penalty dual decomposition (PDD) approach for BD-RIS optimization. The simulation results demonstrate that: (1) the proposed prediction method accurately tracks the position and velocity of the target in dynamic environments; (2) the proposed AO algorithm is efficient and effective, exhibiting fast convergence and achieving a performance improvement of 6.7

$\%$

compared to conventional diagonal RIS.

查看原文本刊更多论文

超对角线RIS辅助下的运动目标改进ISAC框架：精确定位和高效通信

本文提出了一种利用超对角线RIS （BD-RIS）提高波束形成性能和控制无线传播的创新集成传感与通信（ISAC）框架，用于运动目标检测。在此框架下，我们首先设计了一种基于扩展卡尔曼滤波（EKF）的运动目标跟踪方法，该方法具有精确的协同定位。此外，为了进一步提高传感精度，在通信性能要求的约束下，最小化目标位置和速度的联合后验cram r- rao界（PCRB），保持BD-RIS的正交性和对称性约束。考虑到问题的非凸性，我们将其分解为两个子问题，并使用所提出的交替优化（AO）算法迭代求解。AO算法采用半定松弛（SDR）波束形成方法和惩罚对偶分解（PDD）方法进行BD-RIS优化。仿真结果表明：(1)所提出的预测方法能够准确地跟踪目标在动态环境中的位置和速度；(2)所提出的AO算法高效有效，收敛速度快，与传统对角RIS相比，性能提高6.7美元。

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

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.