Joint User Scheduling and Hybrid Beamforming Design for Massive MIMO LEO Satellite Multigroup Multicast Communication Systems

被引:2
|
作者
Liu, Yang [1 ]
Li, Changqing [2 ]
Li, Jiong [2 ]
Feng, Lu [1 ]
机构
[1] Space Engn Univ, Grad Sch, Beijing 101416, Peoples R China
[2] Space Engn Univ, Space Informat Sch, Beijing 101416, Peoples R China
基金
中国国家自然科学基金;
关键词
LEO satellite communications; massive MIMO; multigroup multicast; user scheduling; hybrid beamforming; robust; joint design; energy efficiency; OPTIMIZATION;
D O I
10.3390/s22186858
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
In the satellite multigroup multicast communication systems based on the DVB-S2X standard, due to the limitation of the DVB-S2X frame structure, user scheduling and beamforming design have become the focus of academic research. In this work, we take the massive multi-input multi-output (MIMO) low earth orbit (LEO) satellite communication system adopting the DVB-S2X standard as the research scenario, and the LEO satellite adopts a uniform planar array (UPA) based on the fully connected hybrid structure. We focus on the coupling design of user scheduling and beamforming; meanwhile, the scheme design takes the influence of residual Doppler shift and phase disturbance on channel errors into account. Under the constraints of total transmission power and quality of service (QoS), we study the robust joint user scheduling and hybrid beamforming design aimed at maximizing the energy efficiency (EE). For this problem, we first adopt the hierarchical clustering algorithm to group users. Then, the semidefinite programming (SDP) algorithm and the concave convex process (CCCP) framework are applied to tackle the optimization of user scheduling and hybrid beamforming design. To handle the rank-one matrix constraint, the penalty iteration algorithm is proposed. To balance the performance and complexity of the algorithm, the user preselected step is added before joint design. Finally, to obtain the digital beamforming matrix and the analog beamforming matrix in a hybrid beamformer, the alternative optimization algorithm based on the majorization-minimization framework (MM-AltOpt) is proposed. Numerical simulation results show that the EE of the proposed joint user scheduling and beamforming design algorithm is higher than that of the traditional decoupling design algorithms.
引用
收藏
页数:31
相关论文
共 50 条
  • [21] Beamforming Design and User Grouping for FDD Massive MIMO Systems
    Jeon, Yo-Seb
    Ku, Hwan-Seok
    Lee, Namyoon
    2017 INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY CONVERGENCE (ICTC), 2017, : 439 - 443
  • [22] Joint User Grouping and Beamforming for Low Complexity Massive MIMO Systems
    Chen, Junting
    Gesbert, David
    2016 IEEE 17TH INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS (SPAWC), 2016,
  • [23] Outage Constrained Robust Multigroup Multicast Beamforming for Multi-Beam Satellite Communication Systems
    You, Li
    Liu, Ao
    Wang, Wenjin
    Gao, Xiqi
    IEEE WIRELESS COMMUNICATIONS LETTERS, 2019, 8 (02) : 352 - 355
  • [24] Joint Multicast Beamforming and Relay Design for Maritime Communication Systems
    Duan, Ruiyang
    Wang, Jingjing
    Zhang, Hongming
    Ren, Yong
    Hanzo, Lajos
    IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING, 2020, 4 (01): : 139 - 151
  • [25] Joint multicast beamforming and user scheduling in large-scale antenna systems
    Zhou, Longfei
    Xu, Zi
    Jiang, Wei
    Luo, Wu
    IET COMMUNICATIONS, 2018, 12 (11) : 1307 - 1314
  • [26] Joint Optimization of Hybrid Beamforming for Multi-User Massive MIMO Downlink
    Li, Zheda
    Han, Shengqian
    Sangodoyin, Seun
    Wang, Rui
    Molisch, Andreas F.
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2018, 17 (06) : 3600 - 3614
  • [27] Hybrid Beamforming for Downlink Massive MIMO Systems with Multiantenna User Equipment
    Payami, Sohail
    Ghoraishi, Mir
    Dianati, Mehrdad
    2017 IEEE 86TH VEHICULAR TECHNOLOGY CONFERENCE (VTC-FALL), 2017,
  • [28] Joint User Grouping and Resource Allocation for LEO Satellite Multicast
    Li, Yuwei
    Zhu, Shibing
    Dai, Jianmei
    IEEE SYSTEMS JOURNAL, 2023, 17 (03): : 4695 - 4702
  • [29] Robust Precoding for Massive MIMO LEO Satellite Integrated Communication and Localization Systems
    Zhu, Yongxiang
    You, Li
    Zhou, Huibin
    Jin, Zhenzhou
    Kong, Qingfu
    Gao, Xiqi
    IEEE COMMUNICATIONS LETTERS, 2025, 29 (01) : 21 - 25
  • [30] Joint Machine Learning based Resource Allocation and Hybrid Beamforming Design for Massive MIMO Systems
    Ahmed, Irfan
    Khammari, Hedi
    2018 IEEE GLOBECOM WORKSHOPS (GC WKSHPS), 2018,