Fairness aware secure energy efficiency maximization for UAV-assisted data collection in backscattering networks

Abstract

Autonomous vehicles for intelligent surveillance in rural areas increasingly demand low-cost and reliable data collection technologies to perform dense monitoring across extended areas. Backscattering communication has been employed for this purpose, primarily for low-cost and energy efficiency reasons. This paper considers a backscattering data collection system empowered by unmanned aerial vehicles (UAVs) to overcome the challenge of wireless coverage and provide backscattering tags with physical-layer security. Relevant prior works only focused on the secrecy of backscattering communications, while the limited battery of UAVs was overlooked during the underlying vehicle control. This paper aims to jointly optimize the trajectory of multiple UAVs and choice of tags, as well as tags' reflection parameters, to manage data leakage and total energy consumed by UAVs during a round of data collection. Our specific contributions are threefold. (1) We propose a 3D multi-UAV backscattering data collection framework and formulate an optimization problem to maximize the ratio of secrecy across all tags to the power consumption of UAVs subject to some practical constraints. (2) We show that our problem is non-convex and partition it into three sub-problems, transform objective functions, and relax certain constraints to obtain approximate convex problems that yield suboptimal solutions. (3) We evaluate the efficacy of our proposed intelligent security protocol for UAV-assisted data collection, compare its performance with some baseline schemes, our protocal achieve leading performance in terms of secrecy energy efficiency. We also provide the impact of parameters on the secrecy energy efficiency, as well as quantify its complexity via extensive simulations.