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高速移动环境下OTSM迭代检测算法研究

李国军 龙锟 叶昌荣 梁佳文

李国军, 龙锟, 叶昌荣, 梁佳文. 高速移动环境下OTSM迭代检测算法研究[J]. 电子与信息学报, 2023, 45(6): 2098-2104. doi: 10.11999/JEIT220541
引用本文: 李国军, 龙锟, 叶昌荣, 梁佳文. 高速移动环境下OTSM迭代检测算法研究[J]. 电子与信息学报, 2023, 45(6): 2098-2104. doi: 10.11999/JEIT220541
LI Guojun, LONG Kun, YE Changrong, LIANG Jiawen. Research on OTSM Iterative Detection Algorithm in High-speed Mobile Environment[J]. Journal of Electronics & Information Technology, 2023, 45(6): 2098-2104. doi: 10.11999/JEIT220541
Citation: LI Guojun, LONG Kun, YE Changrong, LIANG Jiawen. Research on OTSM Iterative Detection Algorithm in High-speed Mobile Environment[J]. Journal of Electronics & Information Technology, 2023, 45(6): 2098-2104. doi: 10.11999/JEIT220541

高速移动环境下OTSM迭代检测算法研究

doi: 10.11999/JEIT220541
基金项目: 国家重点研发计划(2019YFC1511300),重庆市基础研究与前沿探索项目(cstc2021ycjh-bgzxm0072)
详细信息
    作者简介:

    李国军:男,教授,研究方向为复杂恶劣环境超视距无线通信与网络

    龙锟:男,硕士生,研究方向为信道均衡

    叶昌荣:男,讲师,研究方向为信号处理

    梁佳文:男,硕士生,研究方向为信道均衡

    通讯作者:

    叶昌荣 yecr@cqupt.edu.cn

  • 中图分类号: TN926

Research on OTSM Iterative Detection Algorithm in High-speed Mobile Environment

Funds: The National Key R& D Program of China (2019YFC1511300), Chongqing Basic Research and Frontier Exploration Project (cstc2021ycjh-bgzxm0072)
  • 摘要: 正交时序复用( Orthogonal Time Sequency Multiplexing, OTSM)通过级联时分和沃尔什-哈达玛(WHT)复用将信息符号在时延和序列域进行复用。由于WHT在调制解调过程不需要进行复杂的乘法运算,相比于正交时频空(OTFS)调制有更低的调制复杂度。该文针对高速移动环境下的OTSM系统提出了一种二级均衡器:首先利用信道矩阵的稀疏性和带状结构在时域逐块进行低复杂度MMSE检测;随后采用高斯-赛德尔(GS)迭代检测进一步消除残余符号干扰。仿真结果表明,所提算法与基于单抽头频域均衡的GS迭代检测算法相比,采用16QAM调制且误码率为10–4时有1.8 dB性能增益。
  • 图  1  不同离散信息符号域与相应调制方案之间的关系

    图  2  SM系统收发模型

    图  3  接收机信号处理流程

    图  4  SM系统在不同检测算法下的误码性能

    图  5  SM系统在不同系统参数下的误码性能

    图  6  不同速度下基于单抽头均衡的GS迭代检测和所提算法的误码性能比较

    图  7  基于单抽头均衡的GS迭代OTSM与OTFS检测和所提算法误码性能比较

    图  8  所提算法在不同用户移动速度和信噪比下的误码性能

    算法1 前向替换算法
     计算${{\boldsymbol{r}}^{(1)} } = {{\boldsymbol{L}}^{ - 1} }{\boldsymbol{r}}$
     1:输入:下三角矩阵${{\boldsymbol{L}}_{M \times M} }$和${{\boldsymbol{r}}_{M \times 1} }$
     2:输出:${\boldsymbol{r}}_{M \times 1}^{(1)} = {\boldsymbol{L}}_{M \times M}^{ - 1}{{\boldsymbol{r}}_{M \times 1} }$
     3:${{\boldsymbol{r}}^{(1)} }(0) = {\boldsymbol{r}}(0)$
     4:for$k = 1:\alpha - 1$ do
     5:${{\boldsymbol{r}}^{(1)} }(k) = {\boldsymbol{r}}(k) - \displaystyle\sum _{i = 1}^k{\boldsymbol{L}}(k,k - i){{\boldsymbol{r}}^{(1)} }(k - i)$
     6:end
     7:for$k = \alpha :M - 1$ do
     8:${{\boldsymbol{r}}^{(1)} }(k) = {\boldsymbol{r}}(k) - \displaystyle\sum _{i = 1}^{\alpha - 1}{\boldsymbol{L}}(k,k - i){{\boldsymbol{r}}^{(1)} }(k - i)$
     9:end
    下载: 导出CSV
    算法2 后向替换算法
     计算${{\boldsymbol{r}}^{(2)} } = {{\boldsymbol{U}}^{ - 1} }{{\boldsymbol{r}}^{(1)} }$
     1:输入:上三角矩阵${{\boldsymbol{U}}_{M \times M} }$和${{\boldsymbol{r}}^{(1)} }_{M \times 1}$
     2:输出:${\boldsymbol{r}}_{M \times 1}^{(2)} = {\boldsymbol{U}}_{M \times M}^{ - 1}{\boldsymbol{r}}_{M \times 1}^{(1)}$
     3:${{\boldsymbol{r}}^{(2)} }(M - 1) = \frac{ { {{\boldsymbol{r}}^{(1)} }(M - 1)} }{ {{\boldsymbol{U}}(M - 1,M - 1)} }$
     4:for$k = M - 2:M - \alpha $do
     5:${ {\boldsymbol{r} }^{(2)} }(k) = \dfrac{1}{ { {\boldsymbol{U} }(k,k)} }[{ {\boldsymbol{r} }^{(1)} }(k) - \displaystyle\sum _{i = 1}^{M - k - 1}{\boldsymbol{U} }(k,k + i){ {\boldsymbol{r} }^{(2)} }(k + i)]$
     6:end
     7:for$k = M - \alpha - 1:0$do
     8:${ {\boldsymbol{r} }^{(2)} }(k) = \dfrac{1}{ { {\boldsymbol{U} }(k,k)} }[{ {\boldsymbol{r} }^{(1)} }(k) - \displaystyle\sum _{i = 1}^{\alpha - 1}{\boldsymbol{U} }(k,k + i){ {\boldsymbol{r} }^{(2)} }(k + i)]$
     9:end
    下载: 导出CSV

    表  1  所提接收机中不同操作的计算复杂度

    操作所需复乘次数
    低复杂度LU分解$[{\alpha ^2} + 2\alpha ]MN$
    前向替换算法$N \left[M\alpha - \dfrac{ { {\alpha ^2} } }{2} + \dfrac{\alpha }{2} - 1 \right]$
    反向替换算法$N \left[M(\alpha - 1) - \dfrac{ { {\alpha ^2} } }{2} + \dfrac{\alpha }{2}\right]$
    稀疏矩阵向量乘法$P(\beta + 1)MN$
    下载: 导出CSV

    表  2  仿真参数

    参数
    调制方式16QAM
    $N$16
    $M$128
    载波频率4 GHz
    子载波间隔15 kHz
    信道模型EVA[20]
    用户移动速度500 km/h
    信道估计理想估计
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-05-05
  • 修回日期:  2022-09-15
  • 网络出版日期:  2022-10-13
  • 刊出日期:  2023-06-10

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