Secondary signal detection algorithm for high-speed mobile environments

doi:10.11772/j.issn.1001-9081.2023050580

Journal of Computer Applications ›› 2024, Vol. 44 ›› Issue (4): 1236-1241.DOI: 10.11772/j.issn.1001-9081.2023050580

Special Issue: 网络与通信

• Network and communications • Previous Articles Next Articles

Secondary signal detection algorithm for high-speed mobile environments

Huahua WANG, Xu ZHANG(), Feng LI

School of Communications and Information Engineering，Chongqing University of Posts and Telecommunications，Chongqing 400065，China

Received:2023-05-15 Revised:2023-06-08 Accepted:2023-06-09 Online:2023-08-01 Published:2024-04-10
Contact: Xu ZHANG
About author:WANG Huahua， born in 1981， M. S.， senior engineer. His research interests include mobile communication baseband signal processing.
ZHANG Xu， born in 1998， M. S. candidate. His research interests include channel equalization.
LI Feng， born in 1999， M. S. candidate. His research interests include orthogonal time frequency space modulation， physical layer algorithm.
Supported by:
Chongqing Natural Science Foundation(cstc2021jcyj-msxmX0454)

面向高速移动环境的二级信号检测算法

王华华, 张旭(), 李峰

重庆邮电大学通信与信息工程学院，重庆 400065

通讯作者: 张旭
作者简介:王华华（1981—），男，重庆人，高级工程师，硕士，主要研究方向：移动通信基带信号处理
张旭（1998—），男，江西上饶人，硕士研究生，主要研究方向：信道均衡；1971415548@qq.com
李峰（1999—），男，河南三门峡人，硕士研究生，主要研究方向：正交时频空间调制、物理层算法。
基金资助:
重庆市自然科学基金资助项目(cstc2021jcyj?msxmX0454)

Abstract

Abstract:

Orthogonal Time Sequency Multiplexing （OTSM） achieves transmission performance similar to Orthogonal Time Frequency Space （OTFS） modulation with lower complexity， providing a promising solution for future high-speed mobile communication systems that require low complexity transceivers. To address the issue of insufficient efficiency in existing time-domain based Gauss-Seidel （GS） iterative equalization， a secondary signal detection algorithm was proposed. First， Linear Minimum Mean Square Error （LMMSE） detection with low complexity was performed in the time domain， and then Successive Over Relaxation （SOR） iterative algorithm was used to further eliminate residual symbol interference. To further optimize convergence efficiency and detection performance， the SOR algorithm was linearly optimized to obtain an Improved SOR （ISOR） algorithm. The simulation experimental results show that compared with SOR algorithm， ISOR algorithm improves detection performance and accelerates convergence while increasing lower complexity. Compared with GS iterative algorithm， ISOR algorithm has a gain of 1.61 dB when using 16 QAM modulation with a bit error rate of $10 - 4$ .

Key words: Orthogonal Time Sequency Multiplexing (OTSM), Orthogonal Time Frequency Space (OTFS) modulation, Successive Over Relaxation (SOR), signal detection, Linear Minimum Mean Square Error (LMMSE), symbol interference

摘要：

正交时间序列复用（OTSM）可以以更低的复杂度实现类似正交时频空间（OTFS）调制的传输性能，为未来需要低复杂度收发器的高速移动性通信系统提供一种有前景的解决方法。针对现有的基于时域的高斯-赛德尔（GS）迭代均衡效率不高的问题，提出二级信号检测算法。首先在时域进行低复杂度线性最小均方误差（LMMSE）检测，其次采用连续超松弛（SOR）迭代算法进一步消除残余符号干扰。为进一步提高收敛效率和检测性能，对SOR算法进行线性优化得到改进SOR（ISOR）算法。仿真实验结果表明，与SOR算法相比，ISOR算法在增加较低复杂度前提下可以提升检测性能并加快算法收敛。与GS迭代算法相比，ISOR算法采用16QAM调制且误码率为 $10 - 4$ 时有1.61 dB的增益。

关键词: 正交时间序列复用, 正交时频空间调制, 连续超松弛, 信号检测, 线性最小均方误差, 符号干扰

CLC Number:

TN926

Huahua WANG, Xu ZHANG, Feng LI. Secondary signal detection algorithm for high-speed mobile environments[J]. Journal of Computer Applications, 2024, 44(4): 1236-1241.

王华华, 张旭, 李峰. 面向高速移动环境的二级信号检测算法[J]. 《计算机应用》唯一官方网站, 2024, 44(4): 1236-1241.

Figures/Tables 12

Fig. 1 Schematic diagram of signal delay extension and Doppler expansion in high-speed mobile environment

Fig. 2 Relationship between different discrete information symbol domains and modulation schemes

Tab. 1 OTSM key variables

参数	含义
$X ∈ C M × N$	发送端二维时延序列信息符号
$x m ∈ C N × 1$	发送端时延序列向量
$X ˜$	发送端二维时延时间矩阵
$x ˜ m = W N ⋅ x m$	发送端时延时间向量
$s = v e c (X ˜)$	发送端时域符号向量
$s n = C M × 1$	时域块
$Y ∈ C M × N$	接收端二维时延序列信息符号
$y m ∈ C N × 1$	接收端时延序列域向量
$Y ˜$	接收端二维时延时间矩阵
$y ˜ m = W N ⋅ y m$	接收端时延时间向量
$r ∈ C N M × 1$	接收端时域符号向量
$r n ∈ C M × 1$	时域块信号
$T f = N T$	OTSM帧总持续时间
$B = M Δ f$	OTSM帧总带宽
$G ∈ C N M × N M$	时域离散信道模型

Tab. 1 OTSM key variables

参数	含义
$X ∈ C M × N$	发送端二维时延序列信息符号
$x m ∈ C N × 1$	发送端时延序列向量
$X ˜$	发送端二维时延时间矩阵
$x ˜ m = W N ⋅ x m$	发送端时延时间向量
$s = v e c (X ˜)$	发送端时域符号向量
$s n = C M × 1$	时域块
$Y ∈ C M × N$	接收端二维时延序列信息符号
$y m ∈ C N × 1$	接收端时延序列域向量
$Y ˜$	接收端二维时延时间矩阵
$y ˜ m = W N ⋅ y m$	接收端时延时间向量
$r ∈ C N M × 1$	接收端时域符号向量
$r n ∈ C M × 1$	时域块信号
$T f = N T$	OTSM帧总持续时间
$B = M Δ f$	OTSM帧总带宽
$G ∈ C N M × N M$	时域离散信道模型

Fig. 3 System model and time-domain input-output relationship

Fig. 4 Time-domain channel matrix

Fig. 5 Secondary signal detection process

Tab. 2 System simulation parameters

参数	值	参数	值
子载波数 $M$	64	调制方式	4QAM，16QAM，64QAM
符号数 $N$	8，16，32	信道模型	扩展车辆信道模型^［16］
载波频率	4 GHz	最大时延扩展	4^［4］
子载波间隔	15 kHz	信道估计	理想估计^［17］
移动速度	0~800 $k m / h$	信道多普勒频谱	Jakes

Tab. 2 System simulation parameters

参数	值	参数	值
子载波数 $M$	64	调制方式	4QAM，16QAM，64QAM
符号数 $N$	8，16，32	信道模型	扩展车辆信道模型^［16］
载波频率	4 GHz	最大时延扩展	4^［4］
子载波间隔	15 kHz	信道估计	理想估计^［17］
移动速度	0~800 $k m / h$	信道多普勒频谱	Jakes

Fig. 6 Performance charts with different w values （N×M=16×64）

Fig. 7 Detection performance comparison among different algorithms （N×M=16×64）

Fig. 8 Iteration number comparison between ISOR and SOR （N×M=16×64）

Fig. 9 BER performance comparison of different algorithms at different speeds （N×M=16×64）

Fig. 10 ISOR BER performance comparison with different parameters N and M

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Secondary signal detection algorithm for high-speed mobile environments

面向高速移动环境的二级信号检测算法

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Figures/Tables 12

References 17

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