🤖 AI Summary
This study addresses the fundamental trade-off between reliability and covertness in wireless covert communications under channel and noise uncertainty. Focusing on quasi-static fading scenarios, it investigates reliability characterized by outage probability and covertness evaluated via radiometer detection. By modeling uncertainties with bounded sets and employing a conditional large-N mid-point threshold radiometer proxy, the work reveals that reliability and covertness are governed by distinct worst-case conditions. Building on this insight, a conflict-aware robust design framework is proposed, yielding closed-form expressions for the robust feasible transmit power and optimal transmission rate. Numerical results demonstrate that uncertainty substantially shrinks the system’s feasible region and degrades performance, while the proposed proxy model achieves high accuracy at low effective signal-to-noise ratios.
📝 Abstract
Covert wireless communication aims to establish a reliable link while hiding the transmission from an adversary. In wireless settings, uncertainty plays a central role in this tradeoff: it can help mask the signal from a warden, but it also complicates robust system design. This raises a basic question: under bounded uncertainty, are reliability and covertness governed by the same adverse conditions? If not, robust covert design cannot be reduced to a single worst-case environment. In this paper, we study this question in a covert wireless model with quasi-static fading, outage-based reliability at Bob and radiometric detection at Willie. Uncertainty is represented through bounded intervals for Bob's average channel strength and Willie's noise power. To obtain a tractable characterization, we adopt a conditional large-N midpoint-threshold surrogate for Willie's detector, parameterized by a Willie-side fading realization. Within this framework, we show that the reliability constraint is governed by Bob's smallest admissible channel parameter, whereas the covertness constraint is governed by Willie's smallest admissible noise level. This establishes a conflict-aware robust-design principle: the adverse realizations for reliability and covertness differ. Based on this result, we derive closed-form expressions for the robustly feasible transmit power and the corresponding robust optimal rate. Numerical results show that bounded uncertainty contracts the feasible region, monotonically reduces the robust optimal rate, and can cause substantial loss relative to the nominal design. Monte Carlo results further show that the conditional surrogate closely tracks the midpoint-threshold radiometer in the intended low-effective-SNR regime. Overall, the paper shows that even in a streamlined wireless setting, robust covert design requires different adverse-case reasoning for reliability and covertness.