{"title":"Scalable Near-Field Localization Based on Partitioned Large-Scale Antenna Array","authors":"Xiaojun Yuan;Mingchen Zhang;Yuqing Zheng;Boyu Teng;Wenjun Jiang","doi":"10.1109/TWC.2024.3519160","DOIUrl":null,"url":null,"abstract":"This paper studies a localization system, where an extremely large-scale antenna array (ELAA) is deployed at the base station (BS) to locate a user equipment (UE) residing in the near-field (Fresnel) region. We propose a novel algorithm, named array partitioning-based location estimation (APLE), for scalable near-field localization. The APLE algorithm is developed based on the basic assumption that, by partitioning the ELAA into multiple subarrays, the UE can be approximated as in the far-field region of each subarray. We establish a Bayeian inference framework based on the geometric constraints between the UE location and the angles of arrivals (AoAs) at different subarrays. Then, the APLE algorithm is designed based on the message-passing principle for the localization of the UE. APLE exhibits linear computational complexity with the number of BS antennas, leading to a significant reduction in complexity compared to existing methods. We further propose an enhanced APLE (E-APLE) algorithm that refines the location estimate obtained from APLE by following the maximum likelihood principle. The E-APLE algorithm achieves superior localization accuracy compared to APLE while maintaining a linear complexity with the number of BS antennas. Numerical results demonstrate that the proposed APLE and E-APLE algorithms outperform the existing baselines in terms of both localization accuracy and computational complexity.","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"24 3","pages":"2203-2217"},"PeriodicalIF":8.9000,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Wireless Communications","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10815057/","RegionNum":1,"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 studies a localization system, where an extremely large-scale antenna array (ELAA) is deployed at the base station (BS) to locate a user equipment (UE) residing in the near-field (Fresnel) region. We propose a novel algorithm, named array partitioning-based location estimation (APLE), for scalable near-field localization. The APLE algorithm is developed based on the basic assumption that, by partitioning the ELAA into multiple subarrays, the UE can be approximated as in the far-field region of each subarray. We establish a Bayeian inference framework based on the geometric constraints between the UE location and the angles of arrivals (AoAs) at different subarrays. Then, the APLE algorithm is designed based on the message-passing principle for the localization of the UE. APLE exhibits linear computational complexity with the number of BS antennas, leading to a significant reduction in complexity compared to existing methods. We further propose an enhanced APLE (E-APLE) algorithm that refines the location estimate obtained from APLE by following the maximum likelihood principle. The E-APLE algorithm achieves superior localization accuracy compared to APLE while maintaining a linear complexity with the number of BS antennas. Numerical results demonstrate that the proposed APLE and E-APLE algorithms outperform the existing baselines in terms of both localization accuracy and computational complexity.
期刊介绍:
The IEEE Transactions on Wireless Communications is a prestigious publication that showcases cutting-edge advancements in wireless communications. It welcomes both theoretical and practical contributions in various areas. The scope of the Transactions encompasses a wide range of topics, including modulation and coding, detection and estimation, propagation and channel characterization, and diversity techniques. The journal also emphasizes the physical and link layer communication aspects of network architectures and protocols.
The journal is open to papers on specific topics or non-traditional topics related to specific application areas. This includes simulation tools and methodologies, orthogonal frequency division multiplexing, MIMO systems, and wireless over optical technologies.
Overall, the IEEE Transactions on Wireless Communications serves as a platform for high-quality manuscripts that push the boundaries of wireless communications and contribute to advancements in the field.