Stochastic geometry for the analysis of wireless covert networks

Covert systems are designed to operate at a low probability of detection (LPD) in order to provide system protection at the physical layer level. The classical approach to covert communications hides the signal in noise; however, the increasing demand for modern covert systems that provides better protection against intercept receivers (IRs) has shifted the focus to the design of Ad-Hoc covert networks (ACNs) that can hide their transmission in the RF spectrum of primary networks (PNs), like mobile networks. In this paper, we use stochastic geometry to provide a comprehensive analysis for two covertness metrics, namely the aggregate metric and the ratio metric, which are used to quantify covertness from the perspective of the IR and the ACN, respectively. The metrics are used to determine the detectability limits of an ACN by an IR. We also demonstrate how the ratio metric can be used to estimate the average communication distance under certain covertness constraints. Additionally, we show how both metrics can be jointly used to analyze the design of the ACN.