  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.
