Reliable Sub-Nyquist Spectrum Sensing via Conformal Risk Control
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866916262035062784 |
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| author | Lee, Hyojin Park, Sangwoo Simeone, Osvaldo Eldar, Yonina C. Kang, Joonhyuk |
| author_facet | Lee, Hyojin Park, Sangwoo Simeone, Osvaldo Eldar, Yonina C. Kang, Joonhyuk |
| contents | Detecting occupied subbands is a key task for wireless applications such as unlicensed spectrum access. Recently, detection methods were proposed that extract per-subband features from sub-Nyquist baseband samples and then apply thresholding mechanisms based on held-out data. Such existing solutions can only provide guarantees in terms of false negative rate (FNR) in the asymptotic regime of large held-out data sets. In contrast, this work proposes a threshold mechanism-based conformal risk control (CRC), a method recently introduced in statistics. The proposed CRC-based thresholding technique formally meets user-specified FNR constraints, irrespective of the size of the held-out data set. By applying the proposed CRC-based framework to both reconstruction-based and classification-based sub-Nyquist spectrum sensing techniques, it is verified via experimental results that CRC not only provides theoretical guarantees on the FNR but also offers competitive true negative rate (TNR) performance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_17071 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Reliable Sub-Nyquist Spectrum Sensing via Conformal Risk Control Lee, Hyojin Park, Sangwoo Simeone, Osvaldo Eldar, Yonina C. Kang, Joonhyuk Signal Processing Detecting occupied subbands is a key task for wireless applications such as unlicensed spectrum access. Recently, detection methods were proposed that extract per-subband features from sub-Nyquist baseband samples and then apply thresholding mechanisms based on held-out data. Such existing solutions can only provide guarantees in terms of false negative rate (FNR) in the asymptotic regime of large held-out data sets. In contrast, this work proposes a threshold mechanism-based conformal risk control (CRC), a method recently introduced in statistics. The proposed CRC-based thresholding technique formally meets user-specified FNR constraints, irrespective of the size of the held-out data set. By applying the proposed CRC-based framework to both reconstruction-based and classification-based sub-Nyquist spectrum sensing techniques, it is verified via experimental results that CRC not only provides theoretical guarantees on the FNR but also offers competitive true negative rate (TNR) performance. |
| title | Reliable Sub-Nyquist Spectrum Sensing via Conformal Risk Control |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2405.17071 |