Design of Directional Antennas for IoT Physical Layer Security in Ambient Backscatter Communication (AmBC)

Abstract

This thesis investigates a novel antenna system designed to enhance physical-layer security for Internet of Things (IoT) communications using Ambient Backscatter Communication (AmBC). Ambient backscatter leverages existing environmental radio frequency (RF) signals to facilitate sustainable, battery-free, and independent communications, significantly advancing the IoT landscape. Nevertheless, conventional omnidirectional communication techniques are vulnerable to information leakage due to their susceptibility to unauthorized interception. To mitigate these security risks, a dual-antenna architecture is introduced, integrating a microstrip patch antenna array optimized for efficient omnidirectional reception and energy harvesting, with a quasi-Yagi-Uda antenna specifically engineered for directional and secure transmission. System parameters-including gain, bandwidth, side lobe levels (SLL), and Voltage Standing Wave Ratio (VSWR)-are rigorously optimized utilizing advanced evolutionary algorithms, namely the Multi-Objective Genetic Algorithm (MOGA) and Multi-Objective Particle Swarm Optimization (MOPSO). Extensive simulations performed using CST Microwave Studio demonstrate notable enhancements in secrecy capacity, signal integrity, and interference resilience compared to traditional antenna designs. This integrated antenna strategy thereby provides a robust, energy-efficient, and secure solution tailored for dynamic wireless IoT environments. Ultimately, this research furnishes practical insights and foundational guidelines critical for deploying secure, efficient, and scalable IoT infrastructures utilizing ambient backscatter technology.