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Transformer-Based Nonlinear Blind Source Separation for Anti-Jamming in DSSS Satellite Communications.

Xiya Sun1, Changqing Li2, Jiong Li2

  • 1Graduate School, Space Engineering University, Beijing 101416, China.

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Summary

This study introduces a novel nonlinear source-separation method for direct-sequence spread-spectrum (DSSS) satellite anti-jamming. The approach significantly improves signal-to-noise ratio (SI-SNR) and reduces failure rates even under high jamming conditions.

Keywords:
Transformerinterference suppressionnonlinear source separationsatellite communication anti-jamming

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Area of Science:

  • Electrical Engineering
  • Signal Processing
  • Satellite Communications

Background:

  • High-power jamming can saturate satellite receiver front ends, causing nonlinearity.
  • Conventional anti-jamming methods fail due to the violation of linear superposition assumptions.
  • Nonlinear interference degrades satellite signal quality and receiver performance.

Purpose of the Study:

  • To develop an advanced anti-jamming technique for direct-sequence spread-spectrum (DSSS) satellite receivers operating in nonlinear regimes.
  • To address the challenge of separating desired DSSS signals from strong jamming interference in nonlinear environments.
  • To enhance the robustness and performance of satellite receivers against sophisticated jamming attacks.

Main Methods:

  • Formulated dual-receiver DSSS anti-jamming as a nonlinear source-separation problem using stacked I/Q observations.
  • Proposed a time-domain separator combining a convolutional front end and a Transformer encoder.
  • Employed supervised pretraining on synthetic nonlinear mixtures and an optional mixture-only adaptation step for refinement.

Main Results:

  • The proposed method significantly improved the scale-invariant signal-to-noise ratio (SI-SNR) from -4.79 dB to 17.73 dB.
  • Failure rates (SI-SNR < 0 dB) decreased dramatically from 60.7% to 2.3% across diverse test conditions.
  • Enhanced robustness under high jammer-to-signal-ratio (JSR) conditions through oversampling and JSR-aware loss reweighting.

Conclusions:

  • The developed nonlinear source-separation technique effectively combats high-power jamming in satellite receivers.
  • The method offers a robust solution for improving DSSS signal recovery in challenging nonlinear RF environments.
  • Fine-tuning with nonlinear reconstruction consistency and communication priors further boosts performance in blind adaptation scenarios.