Joint Optimization of a UAV's Trajectory and Transmit Power for Covert Communications (1812.00583v2)

Abstract: This work considers covert communications in the context of unmanned aerial vehicle (UAV) networks, aiming to hide a UAV for transmitting critical information out of a scenario that is monitored and where communication is not allowed. Specifically, the UAV as a transmitter intends to transmit information to a legitimate receiver (Bob) covertly in order to avoid being detected by a warden (Willie) with location uncertainties at Bob and/or Willie. In order to enhance the considered covert communication performance, we prefer to jointly optimize the UAV's trajectory and transmit power in terms of maximizing the average covert transmission rate from the UAV to Bob subject to transmission outage constraint and covertness constraint. The formulated optimization problem is difficult to tackle directly due to the intractable constraints. As such, we first employ conservative approximation to transform a constraint into a deterministic form and then apply the first-order restrictive approximation to transform the optimization problem into a convex form. By applying the successive convex approximation (SCA) technique, an efficient iterative algorithm is developed to solve the optimization problem. Our examination shows that the developed joint trajectory and transmit power optimization scheme achieves significantly better covert communication performance as compared to a benchmark scheme.

• The paper proposes a joint optimization framework for a UAV's trajectory and transmit power to maximize covert communication rates to a receiver while minimizing detection by an adversary, utilizing successive convex approximation.
• The proposed joint trajectory and transmit power optimization scheme achieves superior covert communication performance compared to a benchmark optimizing only transmit power.
• A key finding indicates that the UAV strategically positions itself closer to the adversary as the demand for communication covertness increases.

Joint Optimization of a UAV's Trajectory and Transmit Power for Covert Communications

The paper under consideration addresses the problem of covert communications in UAV networks, focusing on hiding the transmission activities of a UAV from a monitoring adversary. The paper examines joint optimization of the UAV's trajectory and transmit power to maximize the average covert transmission rate (ACTR) to a legitimate receiver, Bob, while satisfying specific constraints related to communication covertness and transmission outage probability.

The research introduces a novel optimization framework integrating the principles of covert communication into UAV network designs, particularly relevant in military and secure communication applications. The authors account for the uncertainties in the locations of both the intended receiver (Bob) and the adversarial warden (Willie). By utilizing noncentral chi-square distributions to model these uncertainties, they derive key performance metrics, including a lower bound on the average minimum total error rate at Willie, reflecting the success of covert strategies.

To address the non-convex nature of the problem, the authors employ conservative approximation and approximate the optimization problem into a convex form using first-order restrictive approximations. The problem is solved through the successive convex approximation (SCA) technique, resulting in an iterative algorithm that effectively navigates the solution space.

Key Contributions

1. Extension of Covert Communications: The paper pioneers the concept of using a UAV as a dynamic transmitter in covert communication scenarios, moving beyond traditional static setups, and adapting covert strategies to accommodate UAV mobility.
2. Handling of Location Uncertainty: The paper models and incorporates the location uncertainty of Bob and Willie, with resulting distributions aiding in the estimation of error probabilities critical for the optimization task.
3. Iterative Optimization Approach: By employing the SCA technique, the paper develops an iterative algorithm to enhance the UAV's covert communication performance significantly. The approach not only optimizes the UAV's flight path but also its transmission power allocation over time.

Numerical Analysis and Findings

The proposed joint trajectory and transmit power optimization scheme wins favorably against a benchmark scheme that does not optimize the trajectory, demonstrating superior ACTR under various experimental conditions. This advantage highlights the crucial role of trajectory planning in addition to power control in covert operations involving UAVs.

Furthermore, a counterintuitive finding is the UAV's tendency to gravitate closer to Willie as the covertness demand intensifies. This denotes the strategic balance between maintaining minimal detectability and exploiting favorable communication conditions near the legitimate receiver.

Implications and Future Directions

The paper's findings carry substantial implications for designing secure UAV communication networks, especially in applications requiring high secrecy and reliability under adversarial conditions. The consideration of dynamic, mobile entities in communication networks and optimization strategies framed here could extend to other contexts, like IoT and VANETs, where mobility and security are paramount.

For future exploration, researchers could investigate multi-UAV systems, wherein cooperative strategies might further enhance covert communication capabilities. They might also consider the integration of machine learning techniques to predict dynamic environments and further refine the optimization process, adapting to more complex scenarios with multiple adversaries and heterogeneous network conditions.

In conclusion, the paper enriches the discourse on covert communications by stitching together mobility optimization with signal covertness, laying a robust groundwork for future AI innovations in secure and intelligent UAV networks.