Robust Detection with Low-Complexity SDRs: A Pragmatic Approach

The increasing availability of inexpensive software defined radios (SDRs) allows nowadays to implement cognitive radio (CR) functionalities in large scale networks such as the Internet-of-Things and future 5G systems. In this work, we focus on the spectrum sensing functionality that must take into account the front-end impairments of low-cost devices. Based on the noise model of a real SDR dongle, we address the problem of robust signal detection in the presence of noise power uncertainty and non-flat noise power spectral density (PSD). In particular, we analyze the receiver operating characteristic (ROC) of different known detectors in the presence of such front-end impairments, to understand the performance attainable in a real-world scenario. Based on the analysis, we propose two frequency-domain detectors that are proven to outperform previously proposed spectrum sensing techniques such as, e.g., eigenvalues-based tests.