Rydberg Quantum RF Receivers for Radar, Localization and Wireless Communication

Rydberg-atom sensors are an emerging quantum technology capable of directly measuring radio-frequency electric fields with extreme frequency agility, compact form factors and high phase sensitivity. They have the potential to replace the classical antenna-based RF receivers and create a new paradigm for wireless applications. Recent demonstrations have shown the feasibility of Rydberg-based communication receivers and FMCW radar imaging, but the signal processing foundations required to integrate these sensors into practical radar, localization and wireless communication systems remain largely unexplored.

This PhD will develop system-level models and signal processing frameworks for Rydberg quantum RF receivers. The central objective is to establish an equivalent sensing model that captures the unique constraints and opportunities of atomic receivers, including bandwidth limitations, nonlinearities, noise mechanisms and optical-to-electrical signal conversion. Building on this model, the research will derive sensing-theoretic performance bounds and develop algorithms for radar sensing, localization and communication.

The work will investigate FMCW radar processing, angle-of-arrival estimation, ranging, localization and communication waveforms behave under realistic Rydberg receiver constraints. Emphasis will be placed on understanding how quantum RF front-ends alter conventional estimation theory and what new sensing and communication capabilities may emerge from direct electric-field measurements. 

The expected outcome is a rigorous modelling and algorithmic framework that enables Rydberg sensors to be evaluated and integrated within future wireless systems. In addition to model-based approaches, the research will explore how modern machine learning and artificial intelligence techniques can complement physics-based signal processing for tasks such as sensing enhancement, radar perception, localization and adaptive communication operation. The project aligns strongly with imec roadmaps in communication and sensing while establishing a unique bridge between quantum sensing, wireless signal processing and AI-enabled sensing systems.