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  • ISSN 1006-3080
  • CN 31-1691/TQ

基于贪婪策略的低复杂度功率分配算法

袁伟娜 王艳龙 刘伟婷 郭逸飞 王硕恒

袁伟娜, 王艳龙, 刘伟婷, 郭逸飞, 王硕恒. 基于贪婪策略的低复杂度功率分配算法[J]. 华东理工大学学报(自然科学版), 2021, 47(3): 340-347. doi: 10.14135/j.cnki.1006-3080.20200119002
引用本文: 袁伟娜, 王艳龙, 刘伟婷, 郭逸飞, 王硕恒. 基于贪婪策略的低复杂度功率分配算法[J]. 华东理工大学学报(自然科学版), 2021, 47(3): 340-347. doi: 10.14135/j.cnki.1006-3080.20200119002
YUAN Weina, WANG Yanlong, LIU Weiting, GUO Yifei, WANG Shuoheng. A Low Computational Complexity Power Allocation Algorithm Based on Greedy Policy[J]. Journal of East China University of Science and Technology, 2021, 47(3): 340-347. doi: 10.14135/j.cnki.1006-3080.20200119002
Citation: YUAN Weina, WANG Yanlong, LIU Weiting, GUO Yifei, WANG Shuoheng. A Low Computational Complexity Power Allocation Algorithm Based on Greedy Policy[J]. Journal of East China University of Science and Technology, 2021, 47(3): 340-347. doi: 10.14135/j.cnki.1006-3080.20200119002

基于贪婪策略的低复杂度功率分配算法

doi: 10.14135/j.cnki.1006-3080.20200119002
详细信息
    作者简介:

    袁伟娜(1979-),女,黑龙江绥化人,博士,主要研究方向为移动通信理论及相关技术。E-mail:wnyuan@ecust.edu.cn

  • 中图分类号: TN929.5

A Low Computational Complexity Power Allocation Algorithm Based on Greedy Policy

  • 摘要: 非正交多址(Non-Orthogonal Multiple Access,NOMA)系统中发送端的功率分配算法对系统的吞吐量影响很大,而可以取得最优性能的全空间搜索功率分配(Full Search Power Allocation,FSPA)算法由于较高的复杂度,难以运用到实际系统当中。结合串行干扰消除(Successive Interference Cancellation,SIC)接收机的特点及贪心算法中的局部最优原理,提出了一种基于贪婪策略的功率分配算法。该算法的目标是最大化系统的总吞吐量,具体流程采用树的结构来呈现。自树根开始逐层进行功率分配、局部吞吐量判断、保留最优支路等操作,最后从尾节点返回至根节点的唯一通路即为最终的功率分配情况。仿真实验结果表明,该算法在系统总吞吐量与全空间搜索相差不到1.5%的情况下,成功地将复杂度由随用户数指数级的增长降低到了线性级的增长。与其他算法相比,本文算法也均有不同程度的优势。

     

  • 图  1  NOMA系统频带资源分布

    Figure  1.  Frequency band of NOMA

    图  2  两用户下行链路NOMA系统模型

    Figure  2.  Downlink NOMA system model for two users

    图  3  本文算法树状结构图

    Figure  3.  Tree structure of this paper

    图  4  4个用户的树结构图

    Figure  4.  Tree structure of 4 users

    图  5  3种算法复杂度对比

    Figure  5.  Complexity comparison of three algorithms

    图  6  FSPA与本文算法的吞吐量对比

    Figure  6.  Throughout comparison between FSPA and this paper

    图  7  4种算法总吞吐量对比

    Figure  7.  Overall cell throughout of four algorithms

    图  8  4种算法几何平均吞吐量对比

    Figure  8.  Geometric cell throughout of four algorithms

    图  9  4种算法小区边缘用户吞吐量对比

    Figure  9.  Cell-edge user throughout of four algorithms

    表  1  主要的仿真参数

    Table  1.   Simulation parameters

    ParametersParameter values
    Cell layoutHexagonal grid, 19 cell sites, 3 cell per site, wrap-around
    Carrier frequency /GHz2
    System bandwidth /MHz10
    Inter-site distance /m500
    Minimum distance between user
    and BS /m
    35
    Number of transmit antennas1
    Number of receive antennas2
    Thermal noise density/(d·Bm·Hz−1)−174
    Subcarrier space/kHz15
    Channel estimationideal
    Channel model3GPP
    Maximum Doppler frequency/Hz5.55
    Distance dependent path loss /dB138.1+37.6lg r
    Shadowing correlation0.5(inter site); 1.0(intra site)
    Shadowing standard deviation/dB8
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出版历程
  • 收稿日期:  2019-01-19
  • 网络出版日期:  2020-12-16
  • 刊出日期:  2021-06-30

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