Effect of Phase Shift Errors on the Security of UAV-assisted STAR-RIS IoT Networks

TL;DR

This paper analyzes how phase shift errors in UAV-mounted STAR-RIS systems affect the security of IoT networks, providing analytical expressions and optimization strategies to enhance secrecy performance under practical imperfections.

Contribution

It introduces a model for phase estimation errors using von Mises distribution and derives closed-form secrecy rate expressions, along with an optimization method for UAV placement.

Findings

Phase shift errors degrade secrecy rates.

Optimized UAV placement improves security.

Analytical results validated by simulations.

Abstract

Unmanned aerial vehicles (UAV)-mounted simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) systems can provide full-dimensional coverage and flexible deployment opportunities in future 6G-enabled IoT networks. However, practical imperfections such as jittering and airflow of UAV could affect the phase shift of STAR-RIS, and consequently degrade network security. In this respect, this paper investigates the impact of phase shift errors on the secrecy performance of UAV-mounted STAR-RIS-assisted IoT systems. More specifically, we consider a UAV-mounted STAR-RIS-assisted non-orthogonal multiple access (NOMA) system where IoT devices are grouped into two groups: one group on each side of the STAR-RIS. The nodes in each group are considered as potential Malicious nodes for the ones on the other side. By modeling phase estimation errors using a von Mises distribution, analytical closed-form expressions for the ergodic secrecy rates under imperfect phase adjustment are derived. An optimization problem to maximize the weighted sum secrecy rate (WSSR) by optimizing the UAV placement is formulated and is then solved using a linear grid-based algorithm. Monte Carlo simulations are provided to validate the analytical derivations. The impact of phase estimation errors on system's secrecy performance is analyzed, providing critical insights for the practical realisation of STAR-RIS deployments for secure UAV-enabled IoT networks.