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一种基于FAFT的OFDM信号的新型自动调制识别算法
Yuepeng Li1, Xiaogang Tang2, Lu Wang1
1School of Aerospace Information, Space Engineering University, Beijing, 101416, China.
Scientific reports
|March 5, 2026
概括
我们开发了富里埃自适应波器与注意 (FAFT),用于在5G/6G无线系统中高效的自动调制识别. FAFT通过建模直角频率分割多重复合 (OFDM) 光谱结构来准确地识别调制类型.
科学领域:
- 信号处理 信号处理
- 无线通信无线通信
- 机器学习 机器学习
背景情况:
- 自动调制识别 (AMR) 对于5G和6G等下一代无线网络至关重要.
- 现有的AMR方法往往无法利用与直角频率分割多重复合 (OFDM) 系统固有的独特光谱特征.
- 高效准确的AMR对于管理复杂的无线环境至关重要.
研究的目的:
- 为AMR提出一个新的,参数效率高的框架,该框架明确模拟了OFDM光谱结构.
- 提高AMR系统的性能,特别是在具有挑战性的信号条件下.
- 为在实际的5G/6G部署中提供强大的调制识别解决方案.
主要方法:
- 介绍了富里埃自适应波器与注意 (FAFT),一个框架集成一个可学习的基于FFT的自适应波器和一个轻量级的时间域卷积分支.
- 雇员将注意力转向来自频率和时间领域的保险丝特征.
- 整合了一种新的频域调节器,以改善光谱特征的学习.
主要成果:
- 在基准数据集 (RML2016.10a,RML2016.10b) 和实用的EVAS OFDM数据集上,FAFT表现出具有竞争力的准确性.
- 仅用0.13M参数和39.3M FLOP实现了显著的效率.
- 在低信号噪声比 (SNR) 和多路径色条件下表现出强大的稳定性.
结论:
- 在OFDM系统中,FAFT为AMR提供了一个参数高效和准确的解决方案.
- 拟议的框架显示了在5G/6G无线通信系统中实际实施的巨大潜力.
- 明确建模OFDM光谱结构可以提高AMR的性能和稳定性.
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