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A novel automatic modulation recognition algorithm for OFDM signals based on FAFT.

Yuepeng Li1, Xiaogang Tang2, Lu Wang1

  • 1School of Aerospace Information, Space Engineering University, Beijing, 101416, China.

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Summary
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We developed the Fourier Adaptive Filter with Attention (FAFT) for efficient automatic modulation recognition in 5G/6G wireless systems. FAFT accurately identifies modulation types by modeling Orthogonal Frequency Division Multiplexing (OFDM) spectral structures.

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Area of Science:

  • Signal Processing
  • Wireless Communications
  • Machine Learning

Background:

  • Automatic modulation recognition (AMR) is crucial for next-generation wireless networks like 5G and 6G.
  • Existing AMR methods often fail to leverage the distinct spectral characteristics inherent in Orthogonal Frequency Division Multiplexing (OFDM) systems.
  • Efficient and accurate AMR is essential for managing complex wireless environments.

Purpose of the Study:

  • To propose a novel, parameter-efficient framework for AMR that explicitly models OFDM spectral structures.
  • To enhance the performance of AMR systems, particularly in challenging signal conditions.
  • To provide a robust solution for modulation recognition in practical 5G/6G deployments.

Main Methods:

  • Introduced the Fourier Adaptive Filter with Attention (FAFT), a framework integrating a learnable FFT-based adaptive filter and a lightweight time-domain convolutional branch.
  • Employed channel attention to fuse features from the frequency and time domains.
  • Incorporated a novel frequency-domain regularizer to improve spectral feature learning.

Main Results:

  • FAFT demonstrated competitive accuracy on benchmark datasets (RML2016.10a, RML2016.10b) and a practical EVAS OFDM dataset.
  • Achieved remarkable efficiency with only 0.13M parameters and 39.3M FLOPs.
  • Showcased strong robustness under low Signal-to-Noise Ratio (SNR) and multipath fading conditions.

Conclusions:

  • FAFT offers a parameter-efficient and accurate solution for AMR in OFDM systems.
  • The proposed framework shows significant potential for practical implementation in 5G/6G wireless communication systems.
  • Explicitly modeling OFDM spectral structures enhances AMR performance and robustness.