计算机科学 ›› 2023, Vol. 50 ›› Issue (6A): 220400185-7.doi: 10.11896/jsjkx.220400185

• 网络&通信 • 上一篇    下一篇

SWIPT-MISO动态能量消耗模型下能效规划

徐晨阳1, 薛亮1, 王金龙2, 祝龙1   

  1. 1 河北工程大学信息与电气工程学院 河北 邯郸 056038;
    2 福州大学电气工程与自动化学院 福州 350108
  • 出版日期:2023-06-10 发布日期:2023-06-12
  • 通讯作者: 薛亮(liangxue@hebeu.edu.cn)
  • 作者简介:(543552707@qq.com)
  • 基金资助:
    河北省自然科学基金(F2021402009)

Energy Efficiency Planning with SWIPT-MISO Dynamic Energy Consumption Model

XU Chenyang1, XUE Liang1, WANG Jinlong2, ZHU Long1   

  1. 1 School of Information & Electrical Engineering,Hebei University of Engineering,Handan,Hebei 056038,China;
    2 School of Electrical Engineering and Automation,Fuzhou University,Fuzhou 350108,China
  • Online:2023-06-10 Published:2023-06-12
  • About author:XU Chenyang,postgraduate.His main research interests include simultaneous wireless information and power transfer networks. XUE Liang,born in 1982,Ph.D,professor,is a member of China Computer Federation.His main research interests include wireless ad hoc networks,si-multaneous wireless information and power transfer networks,wireless sensor networks.
  • Supported by:
    Natural Science Foundation of Hebei Province,China(F2021402009).

摘要: 无线携能通信网络中发送端获取用户信道状态信息时,会造成时间和频谱资源的浪费。对此,在多用户多输入单输出网络中研究了发送端只有信道分布信息的节能波束形成设计。在信息中断概率、总可用功率以及授权用户可用功率约束下,网络能量效率通过改进的教与学优化算法实现了最大化。此外,针对提出的功率消耗方案,考虑了非线性能量接收机制并提出功率分流机制,使接收机避免进入饱和区,从而提高了功率接收效率。改进的教与学优化算法结合了鲸鱼优化算法的优点,解决了构造得出的非凸优化问题,并提高了收敛速度。仿真实验分析了动态能量分配场景下中断概率、动态功耗系数以及发送端可用功率对系统能量效率的影响,证实了所提算法的有效性。

关键词: 无线携能通信, 能量效率, 非线性能量接收模型, 群智能优化算法

Abstract: In simultaneous wireless information and power transfer networks,multiple antennas are usually equipped at the transmitter,which is able to serve all sensors in one-time transmission over the same frequency band.However,collecting channel state information from all sensors may cause a colossal waste of time and frequency resources.Therefore,the energy-saving beamfor-ming design with only channel distribution information at the transmitter is studied in multi-user multi-input single-output network.Under the constraints of information interruption probability,total available power and available power of authorized users,the network energy efficiency is maximized by the improved teaching-learning-based optimization algorithm.In addition,for the proposed power consumption scheme,the nonlinear energy receiving mechanism is considered,and the power-splitting energy harvesting receiver architecture is proposed to prevent the receiver from entering the saturation region,so as to improve the power receiving efficiency.The improved teaching-learning-based optimization algorithm has the advantages of whale algorithm,solves the constructed nonconvex optimization problem,and improves the convergence speed.Simulation experiments analyze the effects of outage probability,dynamic power consumption coefficient and available power at the transmitter on the system energy efficiency in the dynamic energy allocation scenario,and verify the effectiveness of the proposed algorithm.

Key words: Simultaneous wireless information and power transfer, Energy efficiency, Non-linear energy receiving model, Swarm intelligence optimization algorithm

中图分类号: 

  • TP301
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