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基于SVM的广义空移键控可见光通信系统信号检测算法

商建东 孙浩博 王法松

陈亮, 张雄伟. 一种基于予帧联合编码的600b/s低速语音编码算法[J]. 电子与信息学报, 2003, 25(3): 345-352.
引用本文: 商建东, 孙浩博, 王法松. 基于SVM的广义空移键控可见光通信系统信号检测算法[J]. 电子与信息学报, 2021, 43(10): 2894-2901. doi: 10.11999/JEIT200711
Chen Liang, Zhang Xiongwei. A 600b/s speech coding algorithm based on sub-frame joint coding[J]. Journal of Electronics & Information Technology, 2003, 25(3): 345-352.
Citation: Jiandong SHANG, Haobo SUN, Fasong WANG. SVM-aided Signal Detection in Generalized Space Shift Keying Visible Light Communication System[J]. Journal of Electronics & Information Technology, 2021, 43(10): 2894-2901. doi: 10.11999/JEIT200711

基于SVM的广义空移键控可见光通信系统信号检测算法

doi: 10.11999/JEIT200711
基金项目: 国家自然科学基金(61401401),河南省科技攻关项目(192102210088)
详细信息
    作者简介:

    商建东:男,1968年生,教授,博士生导师,研究方向为高性能计算、计算机网络与通信

    孙浩博:男,1995年生,硕士生,研究方向为可见光通信

    王法松:男,1979年生,教授,硕士生导师,研究方向为盲信号处理、可见光通信

    通讯作者:

    王法松 iefswang@zzu.edu.cn

  • 中图分类号: TN929.12

SVM-aided Signal Detection in Generalized Space Shift Keying Visible Light Communication System

Funds: The National Natural Science Foundation of China (61401401), The Science and Technology Research Project of Henan Province (192102210088)
  • 摘要: 针对室内广义空移键控(GSSK)调制的可见光通信(VLC)系统,该文提出一种基于支持向量机(SVM)的机器学习信号检测算法。在一般的VLC系统中,极大似然(ML)检测是最优检测算法,但是ML检测算法具有很高的计算复杂度。为了解决此问题,该文利用机器学习中的SVM分类思想实现对系统接收端的信号检测,以在保证信号检测正确率的情况下,降低计算复杂度,提高GSSK-VLC系统的信号检测效率。仿真结果表明,该文提出的针对室内GSSK-VLC系统的SVM信号检测算法与ML检测算法相比,在具有接近ML的误比特率(BER)性能的同时,计算复杂度明显降低,有效提升了系统的检测性能。
  • 图  1  室内VLC系统概念图

    图  2  GSSK-VLC系统框图

    图  3  LoS传输的几何模型示意图

    图  4  针对SSK-VLC系统不同算法的BER性能分析

    图  5  针对GSSK-VLC系统的不同算法的BER性能分析

    表  1  GSSK-VLC系统标签

    nlninLED index
    11000LED 1 & 2
    22001LED 1 & 3
    33010LED 1 & 4
    44011LED 1 & 5
    55100LED 2 & 3
    66101LED 2 & 4
    77110LED 2 & 5
    88111LED 3 & 4
    下载: 导出CSV

    表  2  LED位置的空间分布坐标

    4 LEDs8 LEDs
    LED(OX,OY,OZ)m1(1.25, 0.35, 3)
    1(1.25, 1.25, 3)2(3.85, 0.35, 3)
    2(3.25, 1.25, 3)3(1.25, 1.85, 3)
    3(1.35, 3.25, 3)4(3.85, 1.85, 3)
    4(3.25, 3.25, 3)5(1.25, 3.25, 3)
    6(3.85, 3.25, 3)
    7(1.25, 4.25, 3)
    8(3.85, 4.25, 3)
    下载: 导出CSV

    表  3  系统仿真参数设置

    发射端 (LED)接收端(PD)
    LED数量(Nt)4, 8PD数量(Nr)4
    距地面高度3 m距地面高度0.85 m
    半功率半角(ϕ1/2)60PD的物理面积(APD)1cm2
    光学滤波器增益(Ts(ψ))1.0PD的FoV半角(ΨFoV)60
    光电转换效率(η)813.6 μW/mA折光率(β)1.5
    调制指数(α)0.1PD响应度(R)100 μA/mW
    下载: 导出CSV

    表  4  针对GSSK-VLC系统基于不同检测算法所需时间对比

    检测算法计算时间(s)
    KMC175.8836
    KMC (20)3517.6607
    KMC (50)8794.1735
    IKMC879.418
    SVM98.6687
    ML10904.7794
    下载: 导出CSV
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  • 期刊类型引用(2)

    1. 高锐锋,苗艳春,陈颖,王珏,张军,韩瑜,金石. 超大规模MIMO阵列可视区域空间分布数据集. 电子与信息学报. 2024(08): 3063-3072 . 本站查看
    2. 张雷,杨帅,曾琦. 面向可视区域的超大规模MIMO低复杂度混合预编码. 电讯技术. 2024(12): 1931-1938 . 百度学术

    其他类型引用(0)

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出版历程
  • 收稿日期:  2020-08-11
  • 修回日期:  2021-04-15
  • 网络出版日期:  2021-07-14
  • 刊出日期:  2021-10-18

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