Stacked Intelligent Metasurface Enabled LEO Satellite Communications Relying on Statistical CSI

被引:11
作者
Lin, Shining [1 ]
An, Jiancheng [2 ]
Gan, Lu [1 ,3 ]
Debbah, Merouane [4 ]
Yuen, Chau [2 ]
机构
[1] Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Chengdu 611731, Sichuan, Peoples R China
[2] Nanyang Technol Univ, Sch Elect & Elect Engn, Jurong West 639798, Singapore
[3] Yibin Inst UESTC, Sch Informat & Commun Engn, Yibin 644000, Peoples R China
[4] Khalifa Univ Sci & Technol, KU 6G Res Ctr, Abu Dhabi, U Arab Emirates
关键词
Metasurfaces; Low earth orbit satellites; Satellites; Precoding; Satellite broadcasting; Array signal processing; Transmitting antennas; Stacked intelligent metasurface (SIM); LEO satellite; statistical CSI; antenna selection; user grouping;
D O I
10.1109/LWC.2024.3368238
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Low earth orbit (LEO) satellite communication systems have gained increasing attention as a crucial supplement to terrestrial wireless networks due to their extensive coverage area. This letter presents a novel system design for LEO satellite systems by leveraging stacked intelligent metasurface (SIM) technology. Specifically, the lightweight and energy-efficient SIM is mounted on a satellite to achieve multiuser beamforming directly in the electromagnetic wave domain, which substantially reduces the processing delay and computational load of the satellite compared to the traditional digital beamforming scheme. To overcome the challenges of obtaining instantaneous channel state information (CSI) at the transmitter and maximize the system's performance, a joint power allocation and SIM phase shift optimization problem for maximizing the ergodic sum rate is formulated based on statistical CSI, and an alternating optimization (AO) algorithm is customized to solve it efficiently. Additionally, a user grouping method based on channel correlation and an antenna selection algorithm are proposed to further improve the system performance. Simulation results demonstrate the effectiveness of the proposed SIM-based LEO satellite system design and statistical CSI-based AO algorithm.
引用
收藏
页码:1295 / 1299
页数:5
相关论文
共 16 条
  • [11] The Hungarian Method for the assignment problem
    Kuhn, HW
    [J]. NAVAL RESEARCH LOGISTICS, 2005, 52 (01) : 7 - 21
  • [12] Downlink Transmit Design for Massive MIMO LEO Satellite Communications
    Li, Ke-Xin
    You, Li
    Wang, Jiaheng
    Gao, Xiqi
    Tsinos, Christos G.
    Chatzinotas, Symeon
    Ottersten, Bjorn
    [J]. IEEE TRANSACTIONS ON COMMUNICATIONS, 2022, 70 (02) : 1014 - 1028
  • [13] Low-Complexity Hybrid Precoding in Massive Multiuser MIMO Systems
    Liang, Le
    Xu, Wei
    Dong, Xiaodai
    [J]. IEEE WIRELESS COMMUNICATIONS LETTERS, 2014, 3 (06) : 653 - 656
  • [14] All-optical machine learning using diffractive deep neural networks
    Lin, Xing
    Rivenson, Yair
    Yardimei, Nezih T.
    Veli, Muhammed
    Luo, Yi
    Jarrahi, Mona
    Ozcan, Aydogan
    [J]. SCIENCE, 2018, 361 (6406) : 1004 - +
  • [15] MIMO Applications for Multibeam Satellites
    Schwarz, Robert T.
    Delamotte, Thomas
    Storek, Kai-Uwe
    Knopp, Andreas
    [J]. IEEE TRANSACTIONS ON BROADCASTING, 2019, 65 (04) : 664 - 681
  • [16] Antenna Selection for Reconfigurable Intelligent Surfaces: A Transceiver-Agnostic Passive Beamforming Configuration
    Xu, Chao
    An, Jiancheng
    Bai, Tong
    Sugiura, Shinya
    Maunder, Robert G.
    Yang, Lie-Liang
    Di Renzo, Marco
    Hanzo, Lajos
    [J]. IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2023, 22 (11) : 7756 - 7774