On secure UAV-aided ISCC systems

TL;DR

This paper explores the energy-efficient design of UAV-assisted secure integrated communication, sensing, and computing systems, optimizing UAV trajectory, user offloading, and beamforming to enhance secrecy and minimize energy use.

Contribution

It introduces an iterative optimization algorithm for joint UAV trajectory, user scheduling, and beamforming to improve security and energy efficiency in UAV-assisted ISCC systems.

Findings

The proposed algorithm converges quickly and effectively.

Joint optimization significantly reduces total energy consumption.

The system enhances secrecy performance against eavesdroppers.

Abstract

Integrated communication and sensing, which can make full use of the limited spectrum resources to perform communication and sensing tasks simultaneously, is an up-and-coming technology in wireless communication networks. In this work, we investigate the secrecy performance of an uncrewed aerial vehicle (UAV)-assisted secure integrated communication, sensing, and computing system, where the UAV sends radar signals to locate and disrupt potential eavesdroppers while providing offload services to ground users (GUs). Considering the constraints of UAV maximum speed, transmit power, and propulsion energy, as well as secure offloading, data transmission, and computation time, the total energy consumption of GUs is minimized by jointly optimizing user offloading ratio, user scheduling strategy, transmit beamforming, and UAV trajectory. An efficient iterative optimization algorithm is proposed to solve the non-convex optimization problem caused by tightly coupled dependent variables. In particular, the original optimization problem is decomposed into four sub-optimization problems, and the non-convex sub-problems are transformed into approximately convex forms via successive convex approximation. Then, all sub-problems are solved successively by using the block coordinate descent technique. Numerical results demonstrate the convergence and validate the effectiveness of the proposed algorithm.