广东工业大学学报 ›› 2024, Vol. 41 ›› Issue (03): 119-130.doi: 10.12052/gdutxb.230040

• 信息与通信技术 • 上一篇    下一篇

智能反射面辅助认知无线携能通信次用户网络吞吐量优化

乐文英, 崔苗, 张广驰   

  1. 广东工业大学 信息工程学院, 广东 广州 510006
  • 收稿日期:2023-02-28 出版日期:2024-05-25 发布日期:2024-05-25
  • 通信作者: 崔苗(1978-),女,讲师,博士,主要研究方向为电子信息与无线通信技术,E-mail:cuimiao@gdut.edu.cn
  • 作者简介:乐文英(1996-),女,硕士研究生,主要研究方向为智能反射平面和认知无线电等,E-mail:353903450@qq.com
  • 基金资助:
    广东省科技计划项目(2023A0505050127，2022A0505020008，2022A0505050023) ；广东省自然科学基金资助项目(2023A1515011980) ；江西省军民融合北斗通航重点实验室开放基金项目(2022JXRH0004) ；广东省海洋经济发展项目(粤自然资合[2023]24号)

Throughout Optimization for IRS-assisted Cognitive SWIPT Secondary User Networks

Le Wen-ying, Cui Miao, Zhang Guang-chi   

  1. School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2023-02-28 Online:2024-05-25 Published:2024-05-25

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摘要： 为了提高认知无线携能通信(Simultaneous Wireless Information and Power Transfer, SWIPT)网络的频谱利用率并改善其能量受限情况，本文研究智能反射面(Intelligent Reflecting Surface, IRS)辅助的认知SWIPT网络，其中主用户网络以覆盖方式与次用户网络共享频谱，而次用户发射机同时为主用户发射机供能并与次用户接收机传输信息。提出次用户网络吞吐量优化算法，在满足次用户发射机的最大发射功率约束、主用户网络的最小吞吐量约束、总时隙约束以及智能反射面移约束的条件下，联合优化次用户发射机的波束成形矢量、时隙分配和智能反射面反射相移，最大化次用户网络吞吐量。该问题的优化变量相互耦合并且结构高度非凸，难以直接求解。所提算法采用交替优化、半正定松弛以及连续凸逼近方式，将原问题转化为三个子问题进行迭代求解。仿真结果表明与已有基准方案相比，所提算法能明显提高次用户网络的吞吐量。

关键词: 智能反射平面, 认知无线携能通信, 覆盖方式

Abstract: In order to improve the spectrum utilization efficiency and the energy limitation of cognitive simultaneous wireless information and power transfer (SWIPT) network, a study is conducted on an intelligent reflecting surface (IRS) -assisted cognitive SWIPT network, where the primary user network shares its spectrum with the secondary user network in overlay mode, the secondary transmitter simultaneously transmits energy to the primary transmitter and information to the secondary receiver. An optimization algorithm for the throughput of the secondary user network is proposed, under the constraints of the maximum transmit power of the secondary user transmitter, the minimum throughput requirement of the primary user network, the available time slots, and the phase shifts of the IRS, and the beamforming vector of the secondary transmitter, the time slot allocation, and the phase shifts of the IRS are jointly optimized to maximize the throughput of the secondary user network. The optimization variables of the proposed problem are coupled with each other and the structure is highly non-convex, making it is difficult to solve directly. The proposed algorithm applies alternating optimization, semi-positive relaxation, and successive convex approximation techniques to transform the original problem into three subproblems for alternative solution. Simulation results show that the proposed algorithm can significantly improve the throughput of the secondary user network compared with the existing benchmark schemes.

Key words: intelligent reflecting surface, cognitive simultaneous wireless information and power transfer, overlay mode

中图分类号: 

  • TN929.5
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