Joint Autonomous Underwater Vehicle Trajectory and Energy Optimization for Underwater Covert Communications

Underwater covert communication (UCC) technology can prevent legitimate transmission from being intercepted upon by potential eavesdroppers while ensuring a certain rate at the receiver under the condition of underwater acoustic channels. Previous studies have focused on UCC designs that rely on fixed transmitters and receivers, with limited attention given to dynamic moving senders, such as the widely-used autonomous underwater vehicle (AUV). Therefore, the establishment of a secure link between the mobile AUV and the receiver remains unexplored. In this paper, we construct an AUV-aided UCC architecture. Specifically, leveraging the unique characteristics of the underwater environment i.e., time-variant channel, severe attenuation, and ambient noise, the AUV plans its trajectory from the settled start point to the destination, adjusting its transmission power for covert communications. Accounting for both green energy consumption and communication security, we develop a novel multi-objective deep deterministic policy gradient (MODDPG) framework for jointly optimizing AUV's diving energy consumption as well as effective throughput under the covertness constraint. Moreover, we propose an active-trust mechanism at the receiving side to pose an extra safe guard. To handle this, an evolutionary game model between the receiver and eavesdropper is built. Simulations and numerical results demonstrate that our proposed method can achieve a Pareto-optimal solution for covert communications with rapid convergence speed. The evolutionary stable strategy (ESS) enables the receiver to attain superior benefits and security compared to other strategies.