Multi-Beam Design for Near-Field Extremely Large-Scale RIS-Aided Wireless Communications

被引:14
|
作者
Shen, Decai [1 ,2 ]
Dai, Linglong [1 ,2 ]
Su, Xin [3 ]
Suo, Shiqiang [3 ]
机构
[1] Tsinghua Univ, Dept Elect Engn, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Beijing Natl Res Ctr Informat Sci & Technol, Beijing 100084, Peoples R China
[3] CICT Mobile Commun Technol Co Ltd, Innovat Ctr, Beijing 100084, Peoples R China
基金
中国国家自然科学基金;
关键词
Reconfigurable intelligent surface (RIS); constant modulus constraint; multi-beam design; MASSIVE MIMO SYSTEMS; INTELLIGENT;
D O I
10.1109/TGCN.2023.3259579
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
As the energy-saving array composed of passive elements, reconfigurable intelligent surface (RIS) will evolve to the extremely large-scale RIS (XL-RIS) to overcome serious path loss. This change leads to the near-field propagation becoming dominant. There are some works to explore the near-field beam design via beam training. Unfortunately, due to the constant modulus constraint for XL-RIS, most of works in the near-field scenario focus on single-beam design. For massive connectivity requirement scenario, these works will face a serious loss of beam gains, resulting in a decrease in transmission rate. To solve this problem, we propose a block coordinate descent-based scheme with majorization-minimization (MM) algorithm for multi-beam design. The proposed scheme handles constant modulus constraint from two aspects. Firstly, under this constraint, the multi-beam design is an intractable non-convex quadratic programming problem. We utilize MM algorithm to solve this problem as several iterative sub-problems which are easily to be solved. Secondly, the solution space for multi-beam optimization is confined to a limited space due to this constraint, so we introduce the phases for beam gains as an extra optimizable variable to enrich the degree of freedom for optimization. Simulation results show that the proposed scheme could achieve a superior rate 50% higher than the existing schemes.
引用
收藏
页码:1542 / 1553
页数:12
相关论文
共 50 条
  • [1] Multi-Beam Design for Extremely Large-Scale RIS Aided Near-Field Wireless Communications
    Shen, Decai
    Dai, Linglong
    2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022), 2022, : 2426 - 2431
  • [2] RIS-Aided Near-Field MIMO Communications: Codebook and Beam Training Design
    Lv, Suyu
    Liu, Yuanwei
    Xu, Xiaodong
    Nallanathan, Arumugam
    Swindlehurst, A. Lee
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2024, 23 (09) : 12531 - 12546
  • [3] Codebook Design and Beam Training for Extremely Large-Scale RIS: Far-Field or Near-Field?
    Xiuhong Wei
    Linglong Dai
    Yajun Zhao
    Guanghui Yu
    Xiangyang Duan
    ChinaCommunications, 2022, 19 (06) : 193 - 204
  • [4] Codebook design and beam training for extremely large-scale RIS: Far-field or near-field?
    Wei, Xiuhong
    Dai, Linglong
    Zhao, Yajun
    Yu, Guanghui
    Duan, Xiangyang
    CHINA COMMUNICATIONS, 2022, 19 (06) : 193 - 204
  • [5] Near-Field Extremely Large-Scale STAR-RIS Enabled Integrated Sensing and Communications
    Zhou, Jingxuan
    Yang, Yinchao
    Yang, Zhaohui
    Shikh-Bahaei, Mohammad Reza
    IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING, 2025, 9 (01): : 404 - 416
  • [6] Multi-Functional RIS-Aided Wireless Communications
    Wang, Wen
    Ni, Wanli
    Tian, Hui
    IEEE INTERNET OF THINGS JOURNAL, 2023, 10 (23) : 21133 - 21134
  • [7] Near-Field Beam Training for Extremely Large-Scale IRS
    Wang, Tao
    Lv, Jie
    Tong, Haonan
    You, Changsheng
    Yin, Changchuan
    2024 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, WCNC 2024, 2024,
  • [8] Near-Field Tracking with Extremely Large-Scale RIS: A Sparse Learning Approach
    Yuan, Ye
    Chen, Yuanbin
    Guo, Xufeng
    Wang, Ying
    2024 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, WCNC 2024, 2024,
  • [9] Near-field channel estimation for extremely large-scale Terahertz communications
    Yang, Songjie
    Peng, Yizhou
    Lyu, Wanting
    Li, Ya
    He, Hongjun
    Zhang, Zhongpei
    Yuen, Chau
    SCIENCE CHINA-INFORMATION SCIENCES, 2024, 67 (09)
  • [10] Near-Field Communications for Extremely Large-Scale MIMO: A Beamspace Perspective
    Chen, Kangjian
    Qi, Chenhao
    Huang, Jingjia
    Dobre, Octavia A.
    Li, Geoffrey Ye
    IEEE COMMUNICATIONS MAGAZINE, 2025,