Target Sensing-Aided Covert Communication: Reduce Position Randomness

This paper investigates the covert communication in the scenario of counter detection. In traditional covert communication design where the uncertainty of the position of the Warden Willie typically reduces covert performance. To overcome this limitation, we leverage the sensing ability of the ISAC system in a new way to reduce the channel uncertainty between Alice and Willie, thereby enabling less conservative power allocation and significantly improving the achievable covert throughput. In the first stage, the dual functional sensing and communication (DFRC) base station Bob sends joint signals to estimate the azimuth of Willie and transmits information to Alice at the same time. In the second stage, Alice uses the obtained azimuth information of Willie to adjust transmit power while meeting the covert constraints. We build a mathematical model of azimuth angle estimation error and connect it with the Cramér-Rao Bound (CRB) to change it into distance error. This connects sensing accuracy with channel state information (CSI) uncertainty in a linear way, allowing Alice to adopt a higher transmit power while still satisfying the covert constraint, and thus improving the achievable covert throughput. To increase the covert throughput of the user, we use a layered solving strategy to decouple the original problem. First, we use S-procedure to change the constraint on possible distance error into a linear matrix inequality (LMI) constraint and then find the upper limit of transmit power on the user side. Second, we combine it with the uplink communication link rate constraint to find the closed form expression of the resource allocation strategy in vector space. Finally, we use one dimensional search to find the optimal time slot allocation strategy. Simulation results show that the proposed two-stage protocol effectively improves the achievable covert throughput by reducing position uncertainty through sensing.