Joint Trajectory and Power Allocation Design for Secure Artificial Noise aided UAV Communications

TL;DR

This paper proposes a joint optimization framework for UAV trajectory, power, and artificial noise to maximize average secrecy rate, enhancing security in UAV communications against eavesdroppers.

Contribution

It introduces a novel iterative algorithm for joint trajectory and power optimization in UAV security, addressing a complex non-convex problem with guaranteed convergence.

Findings

Significant security improvements over benchmarks.

Effective joint optimization of trajectory and power.

Robust performance under stringent flight durations.

Abstract

This paper investigates an average secrecy rate (ASR) maximization problem for an unmanned aerial vehicle (UAV) enabled wireless communication system, wherein a UAV is employed to deliver confidential information to a ground destination in the presence of a terrestrial passive eavesdropper. By employing an artificial noise (AN) injection based secure two-phase transmission protocol, we aim at jointly optimizing the UAV's trajectory, network transmission power, and AN power allocation over a given time horizon to enhance the ASR performance. Specifically, we divide the original non-convex problem into four subproblems, and propose a successive convex approximation based efficient iterative algorithm to solve it suboptimally with guaranteed convergence. Simulation results demonstrate significant security advantages of our designed scheme over other known benchmarks, particularly for stringent flight durations.