DOA Estimation Assisted by Reconfigurable Intelligent Surfaces

被引:3
|
作者
Chen, Huayang [1 ]
Bai, Yechao [1 ]
Wang, Qiong [1 ]
Chen, Hao [2 ]
Tang, Lan [1 ]
Han, Ping [1 ]
机构
[1] Nanjing Univ, Sch Elect Sci & Engn, Nanjing 210023, Peoples R China
[2] Univ Texas Dallas, Dept Geospaital Informat Sci, Dallas, TX 75080 USA
基金
中国国家自然科学基金;
关键词
Estimation; Direction-of-arrival estimation; Antenna arrays; Target tracking; Sensors; Computer architecture; Azimuth; Array signal processing; direction of arrival (DOA); reconfigurable intelligent surfaces (RISs); target tracking;
D O I
10.1109/JSEN.2023.3273862
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A reconfigurable intelligent surface (RIS)assisted scheme is proposed for direction-of-arrival (DOA) estimation in this work. In the scheme, the RIS is utilized to provide a reflected path, and the RIS-reflected signal is received by array antennas together with the direct-path signal. The model consisting of the direct-path signal and the RIS-reflected signal is proposed, and the Cramer-Rao bound (CRB) is derived based on the signal model to assess the ultimate estimation performance. In order to enhance the estimation performance of RIS-assisted scheme, two possible strategies for the phase design of RIS are presented. The first possibility considers the RIS phase shifts that maximize the coherence of signals from the direct path and the RIS-reflected path. The other possibility considers to obtain the phase shifts that minimize the CRB of DOA estimation in the proposed scheme through a manifold optimization method. Moreover, DOA estimation methods are proposed for the RIS-assisted scheme to validate the scheme feasibility. Target tracking is proposed as a practical application for the RIS-assisted scheme. In the end, both theoretical analysis and simulation results illustrate that the accuracy of DOA estimation and target tracking has been improved with the aid of RIS.
引用
下载
收藏
页码:13433 / 13442
页数:10
相关论文
共 50 条
  • [31] Reconfigurable Intelligent Surfaces Assisted MIMO-MAC with Partial CSI
    Xiong, Jiayuan
    You, Li
    Huang, Yufei
    Ng, Derrick Wing Kwan
    Wang, Wenjin
    Gao, Xiqi
    ICC 2020 - 2020 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2020,
  • [32] Gambling on Reconfigurable Intelligent Surfaces
    Schwarz, Stefan
    IEEE COMMUNICATIONS LETTERS, 2024, 28 (04) : 957 - 961
  • [33] Capacity Characterization for Reconfigurable Intelligent Surfaces Assisted Multiple-Antenna Multicast
    Du, Linsong
    Shao, Shihai
    Yang, Gang
    Ma, Jianhui
    Liang, Qingpeng
    Tang, Youxi
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2021, 20 (10) : 6940 - 6953
  • [34] Reconfigurable Intelligent Computational Surfaces for MEC-Assisted Autonomous Driving Networks
    Yang, Bo
    Zhang, Xueyao
    Yu, Zhiwen
    Cao, Xuelin
    Huang, Chongwen
    Alexandropoulos, George C.
    Zhang, Yan
    Debbah, Merouane
    Yuen, Chau
    2024 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, WCNC 2024, 2024,
  • [35] Reconfigurable Intelligent Surfaces Assisted SM-Cooperative NOMA for THz Communications
    Kumar, M. Hemanta
    Sharma, Sanjeev
    Yoganandam, Y.
    Deka, Kuntal
    Kherani, Arzad
    2024 NATIONAL CONFERENCE ON COMMUNICATIONS, NCC, 2024,
  • [36] Hybrid Reconfigurable Intelligent Surfaces-Assisted Near-Field Localization
    Zhang, Xing
    Zhang, Haiyang
    IEEE COMMUNICATIONS LETTERS, 2023, 27 (01) : 135 - 139
  • [37] Reconfigurable Intelligent Surfaces Assisted 6G Communications for Internet of Everything
    Ahmad S.
    Tariq M.
    Jan M.A.
    Song H.
    IEEE Internet of Things Journal, 2024, 11 (18) : 1 - 1
  • [38] Joint Multi-User Channel Estimation for Hybrid Reconfigurable Intelligent Surfaces
    Boiadjieva, Boriana
    Vu, Mai
    ICC 2023-IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, 2023, : 877 - 882
  • [39] Multiple Residual Dense Networks for Reconfigurable Intelligent Surfaces Cascaded Channel Estimation
    Jin, Yu
    Zhang, Jiayi
    Huang, Chongwen
    Yang, Liang
    Xiao, Huahua
    Ai, Bo
    Wang, Zhiqin
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2022, 71 (02) : 2134 - 2139
  • [40] Low-Cost Beamforming and DOA Estimation Based on One-Bit Reconfigurable Intelligent Surface
    Yang, Zihan
    Chen, Peng
    Guo, Ziyu
    Ni, Dahai
    IEEE SIGNAL PROCESSING LETTERS, 2022, 29 : 2397 - 2401