Quantum Computing for Location Determination

Shokry, Ahmed; Youssef, Moustafa

doi:10.48550/arxiv.2106.11751

Cited by 2 publications

(4 citation statements)

References 39 publications

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“…The proposed quantum algorithm can open the door for a new category of algorithms for location tracking and spatial systems [36]- [39]. For example, given the exponential gain in performance of the quantum-based fingerprinting algorithm provided in this paper, one may wonder whether we still need to do clustering of fingerprint locations to reduce the computational requirements or not [49].…”

Section: B Open Challengesmentioning

confidence: 99%

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A Quantum Algorithm for RF-based Fingerprinting Localization Systems

Shokry

Youssef

2022

2022 IEEE 47th Conference on Local Computer Networks (LCN)

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Fingerprinting is one of the mainstream technologies for localization. However, it needs significant storage overhead and running time, preventing it from scaling to support worldwide indoor/outdoor localization.Quantum computing has the potential to revolutionize computation by making some classically intractable problems solvable on quantum computers. In this paper, we propose a quantum fingerprint-based localization algorithm for enabling large-scale location tracking systems, envisioning future era of location tracking and spatial systems. Specifically, we propose a quantum algorithm that provides an exponential enhancement of both the space and running time complexity compared to the traditional classical systems. We give the details of how to build the quantum fingerprint, how to encode the received signal strength (RSS) measurements in quantum particles, and finally; present a quantum algorithm for calculating the cosine similarity between the online RSS measurements and the fingerprint ones.Results from deploying our algorithm in three real testbeds on IBM Quantum Experience machines confirm the ability of our quantum system to get the same accuracy as the classical one but with the potential exponential saving in both space and running time.

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Section: B Open Challengesmentioning

confidence: 99%

“…In this section, we explain the basic concepts of quantum computing that we will use along the paper [36]- [39].…”

Section: Introductionmentioning

confidence: 99%

A Quantum Algorithm for RF-based Fingerprinting Localization Systems

Shokry

Youssef

2022

2022 IEEE 47th Conference on Local Computer Networks (LCN)

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“…In this section, we give a brief background on the basic concepts of quantum computing that we will build on in the rest of the paper [23], [24].…”

Section: Background On Quantum Computingmentioning

confidence: 99%

“…a test RSS vector during the online location tracking phase) and |γ (e.g. a single fingerprint RSS vector) based on the CSWAP gate [4], [23], [24]. In particular, the circuit calculates: where cos(δ, γ) is cosine the angle between the two normalized vectors δ and γ.…”

Section: The Quantum Cosine Similarity Algorithmmentioning

confidence: 99%

Device-independent Quantum Fingerprinting for Large Scale Localization

Shokry,

Youssef

2022

Preprint

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Although RF fingerprinting is one of the most commonly used techniques for localization, deploying it in a ubiquitous manner requires addressing the challenge of supporting a large number of heterogeneous devices and their variations. We present QHFP, a device-independent quantum fingerprint matching algorithm that addresses two of the issues for realizing worldwide ubiquitous large-scale location tracking systems: storage space and running time as well as devices heterogeneity. In particular, we present a quantum algorithm with a complexity that is exponentially better than the classical techniques, both in space and running time. QHFP also has provisions for handling the inherent localization error due to building the large-scale fingerprint using heterogeneous devices. We give the details of the entire system starting from extracting device-independent features from the raw RSS, mapping the classical feature vectors to their quantum counterparts, and showing a quantum cosine similarity algorithm for fingerprint matching.We have implemented our quantum algorithm and deployed it in a real testbed using the IBM Quantum machine simulator. Results confirm the ability of QHFP to obtain the correct estimated location with an exponential improvement in space and running time compared to the traditional classical counterparts. In addition, the proposed device-independent features lead to more than 20% better accuracy in median error. This highlights the promise of our algorithm for future ubiquitous largescale worldwide device-independent fingerprinting localization systems.

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Quantum Computing for Location Determination

Cited by 2 publications

References 39 publications

A Quantum Algorithm for RF-based Fingerprinting Localization Systems

A Quantum Algorithm for RF-based Fingerprinting Localization Systems

Device-independent Quantum Fingerprinting for Large Scale Localization

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