Low-Altitude UAV-Carried Movable Antenna for Joint Wireless Power Transfer and Covert Communications

2025-10-30

AI Summary

To address insufficient communication covertness in low-altitude unmanned aerial vehicle (UAV)-assisted Internet-of-Things (IoT) wireless power transfer (WPT), this paper proposes a mobile-antenna-enhanced WPT-covert communication co-design architecture. It leverages the UAV’s energy signal as a natural cover to simultaneously power distributed IoT nodes and securely transmit information to a legitimate covert receiver. To jointly optimize energy efficiency, covert rate, and UAV propulsion energy consumption, we formulate a multi-objective coupled optimization problem. We then design a soft actor-critic deep reinforcement learning algorithm—MoE-SAC—integrating a sparse mixture-of-experts (MoE) mechanism and action-projection constraints. Simulation results demonstrate that the proposed approach significantly improves total harvested energy and the covert receiver’s achievable rate, while reducing UAV propulsion energy consumption, thereby achieving synergistic gains in energy efficiency, security, and mobility.

Technology Category

• Machine Learning: Mixture of Experts (MoE)
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Learning to Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Security and Privacy: Privacy-enhancing technologies
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

The proliferation of Internet of Things (IoT) networks has created an urgent need for sustainable energy solutions, particularly for the battery-constrained spatially distributed IoT nodes. While low-altitude uncrewed aerial vehicles (UAVs) employed with wireless power transfer (WPT) capabilities offer a promising solution, the line-of-sight channels that facilitate efficient energy delivery also expose sensitive operational data to adversaries. This paper proposes a novel low-altitude UAV-carried movable antenna-enhanced transmission system joint WPT and covert communications, which simultaneously performs energy supplements to IoT nodes and establishes transmission links with a covert user by leveraging wireless energy signals as a natural cover. Then, we formulate a multi-objective optimization problem that jointly maximizes the total harvested energy of IoT nodes and sum achievable rate of the covert user, while minimizing the propulsion energy consumption of the low-altitude UAV. To address the non-convex and temporally coupled optimization problem, we propose a mixture-of-experts-augmented soft actor-critic (MoE-SAC) algorithm that employs a sparse Top-K gated mixture-of-shallow-experts architecture to represent multimodal policy distributions arising from the conflicting optimization objectives. We also incorporate an action projection module that explicitly enforces per-time-slot power budget constraints and antenna position constraints. Simulation results demonstrate that the proposed approach significantly outperforms some baseline approaches and other state-of-the-art deep reinforcement learning algorithms.

Problem

• Joint wireless power transfer and covert communications for IoT
• Maximizing harvested energy and covert rate while minimizing UAV propulsion
• Solving non-convex optimization with conflicting objectives via MoE-SAC algorithm

Innovation

• UAV-carried movable antenna for WPT and covert communications
• Mixture-of-experts-augmented soft actor-critic algorithm
• Action projection module enforcing power and position constraints