Clearing the Underbrush: AI-Enhanced RF Interference Suppression

arXiv:2608.24974 · cs.LG, cs.AI, eess.SP · Submitted 2026-08-25 · Read on arXiv

cs.LG, cs.AI, eess.SP

Submitted: 2026-08-25

Updated: 2026-08-25

Comments: 7 pages, 10 figures, Accepted to the 2026 IEEE Military Communications Conference (MILCOM)

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Transformer — 46× in this paper · explained in 2 episodes
• Quantization — 10× in this paper · explained in 12 episodes
• Finite Scalar Quantization — 5× in this paper
• Accuracy — 2× in this paper · explained in 1 episode
• Orthogonal Frequency-Division Multiplexing — 2× in this paper
• Perceptual Evaluation of Speech Quality — 2× in this paper
• Adaptation — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Log-Spectral Distance — 1× in this paper
• Pruning — 1× in this paper · explained in 4 episodes
• Quadrature Phase Shift Keying — 1× in this paper
• Robustness — 1× in this paper · explained in 5 episodes
• Short-Time Objective Intelligibility — 1× in this paper
• Tokenization — 1× in this paper · explained in 2 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes

Sources

• The Radio-Frequency Transformer for Signal Separation
• Applied AI-Enhanced RF Interference Rejection
• Finite Scalar Quantization: VQ-VAE Made Simple

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