吉林大学学报(信息科学版) ›› 2025, Vol. 43 ›› Issue (5): 1025-1032.

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基于离散相移 IRS 辅助 C-IoT 系统的EE优化设计 

南春萍1a, 沙国辉2, 孙振兴1b, 胥子昂2, 李雪峰2   

  1. 1. 东北石油大学秦皇岛校区a. 基础部;b. 电气信息工程系,河北秦皇岛066004; 2. 东北石油大学电气信息工程学院,黑龙江大庆163318
  • 收稿日期:2024-03-03 出版日期:2025-09-28 发布日期:2025-11-19
  • 作者简介:南春萍(1981— ), 女, 沈阳人, 东北石油大学讲师,博士,主要从事智能反射面辅助无线网络中的波束形成和干扰管理 等研究,(Tel)86-17717150027(E-mail)2824133787@ qq. com
  • 基金资助:
    黑龙江省自然科学基金资助项目(LH2022F004); 东北石油大学青年科学基金资助项目(2020QNQ-05) 

EE Optimization Design of C-IoT Systems Based on Discrete Phase Shift IRS 

NAN Chunping1a, SHA Guohui2, SUN Zhenxing1b, XU Ziang2, LI Xuefeng2    

  1. 1a. Basic Department; 1b. Department of Electrical Information Engineering, Northeast Petroleum University-Qinhuangdao, Qinhuangdao 066004, China; 2. School of Electrical Information and Engineering, Northeast Petroleum University, Daqing 163318, China
  • Received:2024-03-03 Online:2025-09-28 Published:2025-11-19

摘要: 针对多输入多输出认知物联网(C-IoT:Cognitive Internet of Things)系统中出现的高能耗问题, 提出了一种基于智能反射面(IRS: Intelligent Reflecting Surface)辅助的联合波束形成优化算法。 以次用户处的信干噪比和 IRS 处的离散相移为约束条件,构建新的优化准则,通过联合优化次发射机处的主动波束形成矩阵和IRS处的被动波束形成矩阵最大化系统的能量效率。 将复杂的非凸优化问题分解为子问题,分别使用定点迭代法和逐次细化法对子问题进行处理。 仿真结果表明, 在多天线场景下所提算法具有良好的收敛性。 与基准方案相比, 所提算法在多用户情况下有效提高了系统的能量效率。

关键词: 智能反射面, 离散相移, 波束形成优化, 能量效率 

Abstract: Aiming at the high energy consumption problem that exists in multiple-input multiple-output C-IoT (Cognitive Internet of Things) systems, a joint beamforming optimization algorithm based on IRS(Intelligent Reflecting Surface) assistance is proposed. Taking the signal-to-interference-to-noise ratio at the secondary user and the discrete phase shift at the IRS as constraints, a new optimization criterion is constructed to maximize the energy efficiency of system by jointly optimizing the active beamforming matrix at the secondary transmitter and the passive beamforming matrix at the IRS. After decomposing the complex non-convex optimization problem into sub-problems, the fixed-point iteration method and the successive refinement method are used to process the sub- problems respectively. The simulation results show that the proposed algorithm has good convergence in multi- antenna scenarios. Compared to the baseline scheme, the proposed algorithm effectively improves the energy efficiency of the system in multi-user situations.

Key words: intelligent reflecting surface, discrete phase shift, beamforming optimization, energy efficiency

中图分类号: 

  • TP929.5