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

doi:10.11999/JEIT220541

高速移动环境下OTSM迭代检测算法研究

doi: 10.11999/JEIT220541

李国军^{1, 2},
龙锟^{1, 3},
叶昌荣^{1, 2, 4, ,},
梁佳文^{1, 2}

1.
重庆邮电大学超视距可信信息传输研究所重庆 400065
2.
重庆邮电大学光电工程学院重庆 400065
3.
重庆邮电大学通信与信息工程学院重庆 400065
4.
重庆邮电大学光电信息感测与传输技术重庆市重点实验室博士后科研工作站重庆 400065

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
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- 被引次数: 0
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

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

LI Guojun^{1, 2},
LONG Kun^{1, 3},
YE Changrong^{1, 2, 4
, ,},
LIANG Jiawen^{1, 2}

1.
Lab of Beyond LOS Reliable Information Transmission, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2.
School of Optoelectronic Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
3.
School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
4.
Postdoctoral Research Workstation of Chongqing Key Laboratory of Optoelectronic Information Sensing and Transmission Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Funds: The National Key R& D Program of China (2019YFC1511300), Chongqing Basic Research and Frontier Exploration Project (cstc2021ycjh-bgzxm0072)

摘要

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。
- 正交时序复用 /
- 时延-序列域 /
- 沃尔什-哈达玛变换 /
- 高斯-赛德尔迭代检测
Abstract: Orthogonal Time Sequency Multiplexing (OTSM) multiplexes information symbols in the delay-sequence domain through concatenated time division and Walsh-Hadamard multiplexing. Due to the Walsh-Hadamard Transform (WHT) does not require complex multiplication operations in the modulation and demodulation process, it has lower modulation complexity than Orthogonal Time-Frequency Space (OTFS). In this paper, a two-stage equalizer is proposed for OTSM systems in high-speed mobile environments. First, low-complexity MMSE detection is performed block-by-block in the time domain by utilizing the sparsity and band structure of the channel matrix; Then Gauss-Seid (GS) iterative detection further removes residual symbol interference. The simulation results show that, compared with the GS iterative detection algorithm based on single-tap frequency domain equalization, the proposed algorithm has a performance gain of 1.8 dB when 16QAM modulation is used and the bit error rate is 10^–4.
- Orthogonal Time Sequency Multiplexing(OTSM) /
- Delay-sequence domain /
- Walsh-Hadamard transform /
- Gauss Seidel iterative detection

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图 1 不同离散信息符号域与相应调制方案之间的关系

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图 2 SM系统收发模型

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图 3 接收机信号处理流程

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图 4 SM系统在不同检测算法下的误码性能

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图 5 SM系统在不同系统参数下的误码性能

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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

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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

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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

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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

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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

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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	$P(\beta + 1)MN$

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表 2 仿真参数

参数	值
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

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