Abstract: In shared spectrum systems, it is important to be able to localize simultaneously present multiple intruders (unauthorized transmitters) to effectively protect a shared spectrum from malware-based, jamming, or other multi-device unauthorized-usage attacks. We address the problem of localizing multiple intruders using a distributed set of classical radio-frequency (RF) sensors in the context of a shared spectrum system. In contrast to single transmitter localization, multiple transmitter localization (MTL) has not been thoroughly studied. The key challenge in solving the MTL problem comes from the need to separate an aggregated signal received from multiple intruders into separate signals from individual intruders. We solve the problem via a Bayesian-based approach and a deep-learning-based approach.

After addressing multiple transmitter localization with a network of classical RF sensors, we explore using a quantum sensor network for transmitter localization. A quantum sensor network is a network of spatially dispersed sensors that leverage quantum superposition and quantum entanglement. We pose our transmitter localization problem as a quantum state discrimination (QSD) problem and use the positive operator-valued measurement as a tool for localization in a novel way. Then, we address the additional challenge of the impracticality of general quantum measurement by developing new schemes that replace the QSD's measurement operators with trained parameterized hybrid quantum-classical circuits.


Finally, we investigate a problem that is unique in quantum, i.e., optimizing the initial state of detector sensors in quantum sensor networks. We consider a network of quantum sensors, where each sensor is a qubit detector that fires, i.e., its state changes when an event occurs close by. The change in state due to the firing of a detector is given by a unitary operator. The determination of the firing sensor can be posed as a QSD problem which incurs a probability of error depending on the initial state and the measurement operator used. We address the problem of determining the optimal initial state of the quantum sensor network that incurs a minimum probability of error in determining the firing sensor.