Steady State Responses and Energy Detection of an Additive Stochastically Resonant Noise Spectrum Sensing System for DySPAN Cognitive Radios

This paper models and simulates a stochastically resonant (SR) spectrum sensing (SRSS) system which includes propagation channel impacts, the prevailing background noise and a multi-user interference (MUI) component, that is fed by additive SR noise (ASRN). A traditional Neyman-Pearson energy detector is used to develop an equivalent SRSS energy detection on the post-SRSS-processed output signal, which matches the constant false alarm rate (CFAR) of a traditional energy detector. Using a solution of the applicable SRSS stochastic differential equation (SDE), the SRSS energy detection test statistic is computed, from which the steady-state stochastically resonant signal and noise responses are estimated, allowing an applicable SR energy detection threshold to be determined, against which energy detection on the post-SRSSprocessed output signal can be established. We discuss the background theory, analyze the results and briefly address the implications to boost dynamically sharing spectrum by dynamic spectrum access network (DySPAN) cognitive radios (CR).