Conflict-Aware Robust Design for Covert Wireless Communications

TL;DR

This paper investigates the conflicting adverse conditions affecting reliability and covertness in robust covert wireless communication under bounded uncertainties, deriving explicit design principles and demonstrating the impact of uncertainty on system performance.

Contribution

It reveals that reliability and covertness are governed by different worst-case conditions, leading to a conflict-aware robust design framework with closed-form solutions.

Findings

Bounded uncertainty reduces feasible transmit power and optimal rate.

Reliability is governed by Bob's weakest channel; covertness by Willie's weakest noise.

Monte Carlo results confirm the surrogate model's accuracy in low-SNR regimes.

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.