Robust Trajectory and Transmit Power Design for Secure UAV Communications

Abstract: Unmanned aerial vehicles (UAVs) are anticipated to be widely deployed in future wireless communications, due to their advantages of high mobility and easy deployment. However, the broadcast nature of air-to-ground line-of-sight wireless chan- nels brings a new challenge to the information security of UAV- ground communication. This paper tackles such a challenge in the physical layer by exploiting the mobility of UAV via its trajectory design. We consider a UAV-ground communication system with multiple potential eavesdroppers on the ground, where the information on the locations of the eavesdroppers is imperfect. We formulate an optimization problem which maximizes the average worst-case secrecy rate of the system by jointly designing the robust trajectory and transmit power of the UAV over a given flight duration. The non-convexity of the optimization problem and the imperfect location information of the eavesdroppers make the problem difficult to be solved optimally. We propose an iterative suboptimal algorithm to solve this problem efficiently by applying the block coordinate descent method, S-procedure, and successive convex optimization method. Simulation results show that the proposed algorithm can improve the average worst-case secrecy rate significantly, as compared to two other benchmark algorithms without robust design.

• The paper introduces a robust optimization framework that maximizes the average worst-case secrecy rate by jointly optimizing UAV trajectory and transmit power.
• It leverages block coordinate descent, the S-procedure, and successive convex optimization to address non-convexity and uncertainties in eavesdropper locations.
• Simulations show significant security improvements over conventional methods, demonstrating the practical benefits of the proposed approach.

Robust Trajectory and Transmit Power Design for Secure UAV Communications

The paper "Robust Trajectory and Transmit Power Design for Secure UAV Communications" addresses the critical challenge of maintaining secure communication channels in UAV-ground communication systems, specifically when potential eavesdroppers are located on the ground. The inherent broadcast nature of UAV communications introduces significant security vulnerabilities, which this research seeks to mitigate through strategic trajectory and power management at the physical layer.

Problem Formulation and Approach

The researchers present a robust optimization framework to maximize the average worst-case secrecy rate for a UAV-ground communication setup. The communication involves a UAV ("Alice") and a ground node ("Bob"), amid the presence of multiple potential eavesdroppers ("Eves"). The key challenge in this scenario is the non-convex nature of the optimization problem coupled with the imperfect location information of the eavesdroppers. To navigate these complexities, the authors devise an algorithm that applies the block coordinate descent method, the S-procedure, and successive convex optimization. The proposed solution is suboptimal but computationally efficient, allowing it to account for uncertainties in eavesdropper locations—an improvement over existing methods that generally assume perfect knowledge of those positions.

Simulation and Results

The simulation results demonstrate that this robust design can significantly enhance the average worst-case secrecy rate compared to conventional approaches. Specifically, the simulations underscore the advantage of using the proposed robust strategy over non-robust algorithms that either assume perfect location information or entirely ignore the presence of eavesdroppers. This marked improvement is attributed to the algorithm's capability to adapt the UAV's trajectory in real-time, optimizing both its path and transmit power in response to potential interception threats.

Implications and Future Work

Practically, this research has significant implications for enhancing the security of UAV communication systems where location information may be unreliable or inaccurate. By focusing on physical layer security, this study contributes to the development of more resilient UAV communication structures against eavesdropping threats. Theoretically, this work enriches the design paradigm of UAV communication systems by highlighting the interplay between mobility and security.

Future research directions may include exploring machine learning techniques to enhance the prediction accuracy of potential eavesdropper locations or further extending the system model to account for dynamic environments where eavesdroppers themselves are mobile. Additionally, integrating this framework with other layers of the communication protocol stack could yield comprehensive UAV security solutions.

Overall, this paper provides a substantial contribution to the secure design of UAV-ground communication systems, steering the focus towards robust trajectory planning and power allocation amidst imperfect environmental knowledge.