Compressive Spectrum Sensing With 1-Bit ADCs

Efficient wideband spectrum sensing (WSS) is essential for managing spectrum scarcity in wireless communications. However, existing compressed sensing (CS)-based WSS methods require high sampling rates and power consumption, particularly with high-precision analog-to-digital converters (ADCs). Although 1-bit CS with low-precision ADCs can mitigate these demands, most approaches still depend on multi-user cooperation and prior sparsity information, which are often unavailable in WSS scenarios. This paper introduces a non-cooperative WSS method using multicoset sampling with 1-bit ADCs to achieve sub-Nyquist sampling. We analyze the impact of 1-bit quantization on multiband signals, then apply eigenvalue decomposition to isolate the signal subspace from noise, enabling spectrum support estimation without signal reconstruction. The proposed method can efficiently estimate the support of the occupied spectrum without the prior information on sparsity order.