GPU-Accelerated Design and Implementation of a High-Speed Carrier Recovery Algorithm

GAO Ming; YANG Hetian; FU Shaozhong

doi:10.11959/j.issn.1000-0801.DXKX260051

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GPU-Accelerated Design and Implementation of a High-Speed Carrier Recovery Algorithm

更新时间：2026-05-11

- GPU-Accelerated Design and Implementation of a High-Speed Carrier Recovery Algorithm
- Telecommunications Science (2026)
- 作者机构：
  
  西安电子科技大学通信工程学院，陕西西安 710071
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(62171354)
- DOI：10.11959/j.issn.1000-0801.DXKX260051
  CLC：
- Received：16 January 2026，
  
  Revised：2026-03-26，
  
  Accepted：11 May 2026，
- 稿件说明：
移动端阅览
GAO Ming, YANG Hetian, FU Shaozhong. GPU-Accelerated Design and Implementation of a High-Speed Carrier Recovery Algorithm[J/OL]. Telecommunications Science, 2026.
DOI：

GAO Ming, YANG Hetian, FU Shaozhong. GPU-Accelerated Design and Implementation of a High-Speed Carrier Recovery Algorithm[J/OL]. Telecommunications Science, 2026. DOI： 10.11959/j.issn.1000-0801.DXKX260051.

摘要

针对无线通信系统中载波恢复算法复杂度高、在CPU（Central Processing Unit）中运行时实时性差的问题，提出了一种基于GPU（Graphics Processing Unit）的并行高速载波恢复算法。在无线通信系统中，基于FFT变换的粗频偏估计算法结合基于判决引导锁相环（PLL，Phase Locked Loop）的细频偏估计算法是一种典型的载波恢复算法。然而，考虑到PLL中的反馈结构并不适合在GPU中并行运行，提出使用扫频算法代替判决引导的锁相环算法，通过利用GPU的强大并行运行能力提高载波恢复算法的运行速度。在此基础上，基于计算统一设备架构（CUDA，Compute Unified Device Architecture）平台，通过对扫频算法和其在CUDA中采用的并行归约算法进行优化，进一步提高了载波恢复算法的运行速度。仿真结果表明，所提出的基于GPU的并行载波恢复算法在吞吐量和算法性能方面均优于基于CPU的串行载波恢复算法，对于不同的调制方式，其吞吐量可提高20至40多倍，因此更适用于高速场景下的无线通信系统。

Abstract

To address the high complexity of carrier recovery algorithms in wireless communication systems and their poor real-time performance when executed on CPUs (Central Processing Units)

a parallel high-speed carrier recovery algorithm based on GPU (Graphics Processing Unit) is proposed. In wireless communication systems

the combination of a coarse frequency offset estimation algorithm based on FFT and a fine frequency offset estimation algorithm based on a decision-directed phase-locked loop (PLL) constitutes a typical carrier recovery approach. However

considering that the feedback structure inherent in the PLL is not well suited for parallel execution on GPUs

a frequency sweeping algorithm is proposed to replace the decision-directed PLL algorithm

thereby leveraging the powerful parallel processing capability of GPUs to accelerate the carrier recovery process. On this basis

within the Compute Unified Device Architecture (CUDA) platform

the execution speed of the carrier recovery algorithm is further improved by optimizing the frequency sweeping algorithm and its associated parallel reduction algorithm implemented in CUDA. Simulation results demonstrate that the proposed GPU-based parallel carrier recovery algorithm outperforms the CPU-based serial carrier recovery algorithm in terms of both throughput and algorithmic performance. For different modulation schemes

the throughput can be improved by 20 to over 40 times

making it more suitable for wireless communication systems in high-speed scenarios.

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references

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