RadEar: A Self-Supervised RF Backscatter System for Voice Eavesdropping and Separation
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| _version_ | 1866915858581815296 |
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| author | Wang, Qijun Yan, Peihao Qian, Chunqi Zeng, Huacheng |
| author_facet | Wang, Qijun Yan, Peihao Qian, Chunqi Zeng, Huacheng |
| contents | Eavesdropping on voice conversations presents a growing threat to personal privacy and information security. In this paper, we present RadEar, a novel RF backscatter-based system designed to enable covert voice eavesdropping through walls. RadEar consists of two key components: (i) a batteryless RF backscatter tag covertly deployed inside the target space, and (ii) an RF reader located outside the room that performs signal demodulation, voice separation, and denoising. The tag features a compact, dual-resonator design that achieves energy-efficient frequency modulation for continuous voice eavesdropping while mitigating self-interference by separating excitation and reflection frequencies. To overcome the challenges of weak signal reception and overlapping speech, the RF reader employs self-supervised learning models for voice separation and denoising, trained using a remix-based objective without requiring ground-truth labels. We fabricate and evaluate RadEar in real-world scenarios, demonstrating its ability to recover and separate human speech with high fidelity under practical constraints. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_12446 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | RadEar: A Self-Supervised RF Backscatter System for Voice Eavesdropping and Separation Wang, Qijun Yan, Peihao Qian, Chunqi Zeng, Huacheng Networking and Internet Architecture Sound Eavesdropping on voice conversations presents a growing threat to personal privacy and information security. In this paper, we present RadEar, a novel RF backscatter-based system designed to enable covert voice eavesdropping through walls. RadEar consists of two key components: (i) a batteryless RF backscatter tag covertly deployed inside the target space, and (ii) an RF reader located outside the room that performs signal demodulation, voice separation, and denoising. The tag features a compact, dual-resonator design that achieves energy-efficient frequency modulation for continuous voice eavesdropping while mitigating self-interference by separating excitation and reflection frequencies. To overcome the challenges of weak signal reception and overlapping speech, the RF reader employs self-supervised learning models for voice separation and denoising, trained using a remix-based objective without requiring ground-truth labels. We fabricate and evaluate RadEar in real-world scenarios, demonstrating its ability to recover and separate human speech with high fidelity under practical constraints. |
| title | RadEar: A Self-Supervised RF Backscatter System for Voice Eavesdropping and Separation |
| topic | Networking and Internet Architecture Sound |
| url | https://arxiv.org/abs/2603.12446 |