<p>Fingerprinting cellular localization offers high accuracy but is constrained by the current devices’ limited access to neighboring towers, often crucial for precise localization. In this paper, we introduce a practical quantum algorithm for scalable single cell tower localization. The proposed algorithm encodes both the user’s recent cell tower connections IDs (online sequence) and the reference database (offline sequences) into quantum states, enabling efficient quantum search to find the reference location that best matches the user’s current cell tower observations. We present a complete system design, address key implementation challenges, and evaluate our algorithm in a real testbed. Implementation results on the IBM quantum machine simulator demonstrate that our quantum algorithm matches the classical localization accuracy while providing exponential saving in space and quadratic speedup. This highlights the promise of the proposed algorithm for large-scale cellular localization.</p>

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A quantum algorithm for localization using limited cellular information

  • Ahmed Shokry,
  • Moustafa Youssef

摘要

Fingerprinting cellular localization offers high accuracy but is constrained by the current devices’ limited access to neighboring towers, often crucial for precise localization. In this paper, we introduce a practical quantum algorithm for scalable single cell tower localization. The proposed algorithm encodes both the user’s recent cell tower connections IDs (online sequence) and the reference database (offline sequences) into quantum states, enabling efficient quantum search to find the reference location that best matches the user’s current cell tower observations. We present a complete system design, address key implementation challenges, and evaluate our algorithm in a real testbed. Implementation results on the IBM quantum machine simulator demonstrate that our quantum algorithm matches the classical localization accuracy while providing exponential saving in space and quadratic speedup. This highlights the promise of the proposed algorithm for large-scale cellular localization.