In increasingly compact and complex platforms such as satellites, autonomous vehicles, and connected sensors, antennas are no longer isolated components. They are deeply embedded within the system architecture and have a direct impact on overall performance, integration complexity, and physical constraints. This thesis investigates the role of antennas from a system engineering perspective, demonstrating how the early and accurate derivation of system requirements can enable better-informed antenna design choices, leading to improved optimization of size, weight, power, and cost (SWaP-C) across the entire platform.

Through three case studies, this work challenges the traditional focus on antenna miniaturization in isolation, arguing instead for the miniaturization of the entire system through intelligent requirement allocation, cross-domain trade-offs, and functional integration. It explores how specific system demands, such as physical-layer security or radar performance, can translate into non-obvious constraints on antenna performance, placement, and architecture. It is shown how re-allocating system functions from different components into the antenna can reduce complexity and unlock new opportunities for system-level efficiency.

By considering antennas in relation to their system context and treating them as equally important in the system design process, this thesis presents a more unified, efficient, and flexible approach to modern RF system engineering.