Catalyzing Near-field Localization Through RIS Assistance: Optimization of Hybrid Operational Paradigms

doi:10.1109/GLOBECOM52923.2024.10901497

	Catalyzing Near-field Localization Through RIS Assistance: Optimization of Hybrid Operational Paradigms
	Xu Fang; Lixiang Lian
	2024-12-12
会议录名称	GLOBECOM 2024 - 2024 IEEE GLOBAL COMMUNICATIONS CONFERENCE
ISSN	1930-529X
页码	4448-4453
DOI	10.1109/GLOBECOM52923.2024.10901497
摘要	The utilization of reconfigurable intelligent meta-surface (RIS) for target localization has emerged as a prominent technology in sixth-generation (6G) wireless networks. Due to the deployment of large-scale RIS and the application of high-frequency signaling in 6G, future localization scenarios are anticipated to predominantly occur within the near-field region. In this paper, we investigate the scenario of near-field target localization supported by large-scale RIS with hybrid operational paradigms, wherein elements capable of passive or active signal processing (SP) are employed. Through a series of complex technical calculations, we derive the closed-form of Cramer-Rao bound (CRB) for near-field localization assisted by RIS with hybrid operational paradigms. By analyzing the Cramer-Rao bound (CRB) of near-field localization, we aim to optimize the ratio of active and passive SP elements of RIS to determine the optimal hybrid operational paradigms. To achieve this, we utilize a spatial angle approximation technique to convert the complex combinatorial optimization problem into a tractable optimization problem, which is amenable to efficient solutions using existing optimization algorithms. Through simulations, we show that the proposed technique can effectively find the optimal ratio of active and passive SP elements that minimizes the localization error.
关键词	Compressed sensing Image coding Image segmentation Interpolation Crame Rao bounds Crame-Rao lower bounds Cramer Rao lower bound Large-scales Near-field localisation Processing elements Reconfigurable Reconfigurable intelligent surface Signal-processing Target localization
会议名称	2024 IEEE Global Communications Conference, GLOBECOM 2024
会议地点	Cape Town, South Africa
会议日期	8-12 Dec. 2024
URL	查看原文
收录类别	EI
语种	英语
出版者	Institute of Electrical and Electronics Engineers Inc.
EI入藏号	20251318124763
EI主题词	Cramer-Rao bounds
EISSN	2576-6813
EI分类号	716.1 Information Theory and Signal Processing ; 1106.3.1 Image Processing ; 1201.9 Numerical Methods ; 1202.2 Mathematical Statistics
原始文献类型	Conference article (CA)
来源库	IEEE
文献类型	会议论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/496911
专题	信息科学与技术学院信息科学与技术学院_硕士生信息科学与技术学院_PI研究组_廉黎祥组
作者单位	School of Information Science and Technology, ShanghaiTech University, Shanghai, China
第一作者单位	信息科学与技术学院
第一作者的第一单位	信息科学与技术学院
推荐引用方式 GB/T 7714	Xu Fang,Lixiang Lian. Catalyzing Near-field Localization Through RIS Assistance: Optimization of Hybrid Operational Paradigms[C]:Institute of Electrical and Electronics Engineers Inc.,2024:4448-4453.