Dynamic Robust Spectrum Sensing Based on Goodness-of-Fit Test Using Bilateral Hypotheses

Dynamic spectrum detection has attracted increasing interest in drone or controller problems. Spectrum sensing as a promising solution allows us to provide dynamic map within the target frequency band by estimating occupied sub-bands specific period. In this paper, robust Student’s t-distribution model is built tackle scenario with small number of observed samples. Then, relying on characteristics statistical model, we propose an appropriate goodness-of-fit (GoF) test statistic regarding Moreover, obtain reliable sensing, bilateral hypotheses are both used make decision. Numerical simulations show superiority proposed method compared other schemes, including unilateral hypothesis-based GoF testing and conventional energy detection, sample cases.