  Remarkable advances have been achieved in localization techniques in past
decades, rendering it one of the most important technologies indispensable to
our daily lives. In this paper, we investigate a novel localization approach
for future computing by presenting QuERLoc, the first study on localization
using quantum-enhanced ranging. By fine-tuning the evolution of an entangled
quantum probe, quantum ranging can output the information integrated in the
probe as a specific mapping of distance-related parameters. QuERLoc is inspired
by this unique property to measure a special combination of distances between a
target sensor and multiple anchors within one single physical measurement.
Leveraging this capability, QuERLoc settles two drawbacks of classical
localization approaches: (i) the target-anchor distances must be measured
individually and sequentially, and (ii) the resulting optimization problems are
non-convex and are sensitive to noise. We first present the theoretical
formulation of preparing the probing quantum state and controlling its dynamic
to induce a convexified localization problem, and then solve it efficiently via
optimization. We conduct extensive numerical analysis of QuERLoc under various
settings. The results show that QuERLoc consistently outperforms classical
approaches in accuracy and closely follows the theoretical lowerbound, while
maintaining low time complexity. It achieves a minimum reduction of 73% in RMSE
and 97.6% in time consumption compared to baselines. By introducing range-based
quantum localization to the mobile computing community and showing its superior
performance, QuERLoc sheds light on next-generation localization technologies
and opens up new directions for future research.
