Joint Trajectory and Resource Allocation Design for Energy-Efficient Secure UAV Communication Systems (2003.07028v1)

Abstract: In this paper, we study the trajectory and resource allocation design for downlink energy-efficient secure unmanned aerial vehicle (UAV) communication systems, where an information UAV assisted by a multi-antenna jammer UAV serves multiple ground users in the existence of multiple ground eavesdroppers. The resource allocation strategy and the trajectory of the information UAV, and the jamming policy of the jammer UAV are jointly optimized for maximizing the system energy efficiency. The joint design is formulated as a non-convex optimization problem taking into account the quality of service (QoS) requirement, the security constraint, and the imperfect channel state information (CSI) of the eavesdroppers. The formulated problem is generally intractable. As a compromise approach, the problem is divided into two subproblems which facilitates the design of a low-complexity suboptimal algorithm based on alternating optimization approach. Simulation results illustrate that the proposed algorithm converges within a small number of iterations and demonstrate some interesting insights: (1) the introduction of a jammer UAV facilitates a highly flexible trajectory design of the information UAV which is critical to improving the system energy efficiency; (2) by exploiting the spatial degrees of freedom brought by the multi-antenna jammer UAV, our proposed design can focus the artificial noise on eavesdroppers offering a strong security mean to the system.

• The paper introduces a joint trajectory and resource allocation framework that significantly improves energy efficiency in UAV communication systems.
• The study employs a multi-antenna jammer strategy to enhance security by focusing artificial noise on eavesdroppers while maintaining QoS for users.
• The iterative algorithm leveraging SCA and Dinkelbach’s method demonstrates rapid convergence and adaptability across various operational scenarios.

Analyzing Energy-Efficient Secure UAV Communication Systems

UAV-assisted communication systems offer significant promise in addressing the increasing demands for high-data-rate and secure communications, specifically in scenarios constrained by geographical or infrastructural limitations. This paper delves deeply into the design and optimization of such a system, focusing on joint trajectory and resource allocation to maximize energy efficiency and communication security. The authors present a novel paradigm where a multi-antenna jammer UAV assists an information UAV in ensuring secure communications to multiple ground users amidst the presence of eavesdroppers.

Central to this paper is the formulation of a non-convex optimization problem. This problem intricately balances quality of service (QoS) and security constraints while managing the challenge of imperfect channel state information (CSI) available for eavesdroppers. The optimization is tackled via a suboptimal algorithm employing an alternating approach. This divides the original problem into two sub-problems: one focused on resource allocation while keeping UAV trajectories constant, and another optimizing trajectories given fixed resource allocations.

Key Technical Contributions

1. Resource and Trajectory Optimization: The paper details the joint optimization of the UAV trajectory and the resource allocation strategy, which is critical for improving system energy efficiency. This novel approach proposes a framework accommodating the high variability of UAV positions and potential eavesdropper locations.
2. Multi-Antenna Jamming: The use of a multi-antenna jammer UAV introduces significant advantages. By exploiting spatial degrees of freedom, it can focus artificial noise effectively on eavesdroppers, thereby enhancing communication security without adversely affecting legitimate users.
3. Iterative Solution Approach: The authors implement an iterative algorithm, converging quickly to a suboptimal solution. They employ techniques like successive convex approximation (SCA) and Dinkelbach's method, ensuring the algorithm balances computational efficiency and solution accuracy.
4. Practical Evaluation: Simulation results underscore the theoretical claims, depicting rapid convergence and showcasing the system's adaptability to various operational parameters, including different UAV flight times, transmit power levels, and the number of antennas on the jammer UAV.

Theoretical and Practical Implications

This paper sets substantial groundwork for future research in UAV-based secure communication systems. The theoretical contributions significantly clarify the complex dynamics of joint trajectory and resource allocation optimization. Practically, the framework may be foundational for next-generation communication networks where airborne networking platforms will likely play a core role in secure communications, especially in emergency and disaster recovery scenarios.

Future Directions

Potential extensions of this work might investigate optimizing the trajectory of the jammer UAV, considering its impact on system performance. Further research could also explore scenarios with highly mobile eavesdroppers and adaptive methods to handle rapidly changing CSI. Another promising avenue might be the integration of machine learning techniques for dynamic trajectory prediction and resource allocation, further enhancing the adaptability and efficiency of UAV communication systems.

In conclusion, this paper provides a robust structure for energy-efficient, secure UAV communication systems, balancing practical considerations and advanced theoretical modeling. The insights gained pave the way towards the deployment of more secure and efficient airborne networks in various real-world applications.