基于GPU的OMCSS水声通信M元解扩算法并行实现

doi:10.12305/j.issn.1001-506X.2025.03.30

系统工程与电子技术 ›› 2025, Vol. 47 ›› Issue (3): 978-986.doi: 10.12305/j.issn.1001-506X.2025.03.30

基于GPU的OMCSS水声通信M元解扩算法并行实现

彭海源¹^,², 王巍¹, 李德瑞¹^,², 刘彦君¹^,², 李宇¹^,*, 迟骋¹, 田亚男¹

1. 中国科学院声学研究所先进水下信息技术重点实验室, 北京 100190
2. 中国科学院大学, 北京 100049

收稿日期:2024-03-06 出版日期:2025-03-28 发布日期:2025-04-18
通讯作者: 李宇
作者简介:彭海源 (1998—), 男, 博士研究生, 主要研究方向为信号与信息处理、稳健水声通信、扩频水声通信
王巍 (1983—), 男, 研究员, 博士, 主要研究方向为信号与信息处理、水声通信
李德瑞 (1998—), 男, 博士研究生, 主要研究方向为信号与信息处理、多载波水声通信
刘彦君 (2000—), 女, 博士研究生, 主要研究方向为信号与信息处理、阵列水声通信
李宇 (1977—), 男, 研究员, 博士, 主要研究方向为水声信号处理、阵列信号处理、水声通信与网络技术
迟骋 (1989—), 男, 研究员, 博士, 主要研究方向为水声信号处理、水声成像、水下通信及组网、智能感知技术
田亚男 (1995—), 女, 博士后, 主要研究方向为水声通信与组网、信号处理及水下环境噪声
基金资助:
国家自然科学基金(E311130101)

GPU-based parallel implementation of M-ary despreading algorithm for OMCSS underwater acoustic communication

Haiyuan PENG¹^,², Wei WANG¹, Derui LI¹^,², Yanjun LIU¹^,², Yu LI¹^,*, Cheng CHI¹, Yanan TIAN¹

1. Key Laboratory of Science and Technology on Advanced Underwater Acoustic Signal Processing, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
2. University of Chinese Academy of Sciences, Beijing 100049, China

Received:2024-03-06 Online:2025-03-28 Published:2025-04-18
Contact: Yu LI

摘要/Abstract

摘要：

针对正交多载波扩频(orthogonal multi-carrier spread spectrum, OMCSS)水声通信系统接收信号快速处理需求, 提出一种基于图形处理模块(graphic processing unit, GPU)的M元解扩算法的并行实现方法。首先, 分析M元解扩算法在GPU平台上实现的可行性, 针对算法内部基础运算单元进行并行优化处理。然后, 为了进一步提升GPU并行运行速度, 对算法进行基于并发内核执行的M元并行解扩计算架构设计。在中央处理器(central processing unit, CPU)+GPU异构平台上对算法性能进行测试。测试结果表明, 设计的M元并行解扩算法相比M元串行解扩算法在运行速度上有最大90.47%的提升, 最大加速比为10.5。

关键词: 正交多载波扩频, 水声通信, M元解扩, 图形处理模块, 并行实现

Abstract:

In response to the requirements for fast processing of received signals in the orthogonal multi-carrier spread spectrum (OMCSS) underwater acoustic communication system, a parallel implementation of the M-ary despreading algorithm based on the graphic processing unit (GPU) is proposed. First, the feasibility of implementing the M-ary despreading algorithm on the GPU platform is analyzed, and parallel optimization processing is performed on the internal basic computing units of the algorithm. Then, in order to improve the parallel processing speed, M-ary parallel despreading computing architecture based on concurrent kernel execution is designed. The algorithm performance is tested on a central processing unit (CPU)+GPU heterogeneous platform. The test results show that the M-ary parallel despreading algorithm designed in this paper has a maximum improvement of 90.47% in running speed compared to the M-ary serial despreading algorithm, and the maximum speedup ratio is 10.5.

Key words: orthogonal multi-carrier spread spectrum (OMCSS), underwater acoustic communication, M-ary despreading, graphics processing unit (GPU), parallel implementation

中图分类号:

TN929.3

彭海源, 王巍, 李德瑞, 刘彦君, 李宇, 迟骋, 田亚男. 基于GPU的OMCSS水声通信M元解扩算法并行实现[J]. 系统工程与电子技术, 2025, 47(3): 978-986.

Haiyuan PENG, Wei WANG, Derui LI, Yanjun LIU, Yu LI, Cheng CHI, Yanan TIAN. GPU-based parallel implementation of M-ary despreading algorithm for OMCSS underwater acoustic communication[J]. Systems Engineering and Electronics, 2025, 47(3): 978-986.

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参数	CPU	GPU
型号	NVIDIA Carmel ARMv8.2	NVIDIA Volta GPU
核心数量	6-core	384 CUDA cores48 Tensor cores
时钟频率/GHz	1.4	1.1
操作系统	Ubuntu18.04
CUDA版本	CUDA10.2

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基于GPU的OMCSS水声通信M元解扩算法并行实现

GPU-based parallel implementation of M-ary despreading algorithm for OMCSS underwater acoustic communication

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